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Sample records for fabricating convoluted shaped

  1. Automatic construction of statistical shape models using deformable simplex meshes with vector field convolution energy.

    PubMed

    Wang, Jinke; Shi, Changfa

    2017-04-24

    In the active shape model framework, principal component analysis (PCA) based statistical shape models (SSMs) are widely employed to incorporate high-level a priori shape knowledge of the structure to be segmented to achieve robustness. A crucial component of building SSMs is to establish shape correspondence between all training shapes, which is a very challenging task, especially in three dimensions. We propose a novel mesh-to-volume registration based shape correspondence establishment method to improve the accuracy and reduce the computational cost. Specifically, we present a greedy algorithm based deformable simplex mesh that uses vector field convolution as the external energy. Furthermore, we develop an automatic shape initialization method by using a Gaussian mixture model based registration algorithm, to derive an initial shape that has high overlap with the object of interest, such that the deformable models can then evolve more locally. We apply the proposed deformable surface model to the application of femur statistical shape model construction to illustrate its accuracy and efficiency. Extensive experiments on ten femur CT scans show that the quality of the constructed femur shape models via the proposed method is much better than that of the classical spherical harmonics (SPHARM) method. Moreover, the proposed method achieves much higher computational efficiency than the SPHARM method. The experimental results suggest that our method can be employed for effective statistical shape model construction.

  2. Patterned fabric defect detection via convolutional matching pursuit dual-dictionary

    NASA Astrophysics Data System (ADS)

    Jing, Junfeng; Fan, Xiaoting; Li, Pengfei

    2016-05-01

    Automatic patterned fabric defect detection is a promising technique for textile manufacturing due to its low cost and high efficiency. The applicability of most existing algorithms, however, is limited by their intensive computation. To overcome or alleviate the problem, this paper presents a convolutional matching pursuit (CMP) dual-dictionary algorithm for patterned fabric defect detection. A preprocessing with mean sampling is performed to eliminate the influence of background texture of fabric defects. Subsequently, a set of defect-free image blocks are selected as a sample set by sliding window. Dual-dictionary and sparse coefficiencies of the defect-free sample set are obtained via CMP and the K-singular value decomposition (K-SVD) based on a Gabor filter. Then we employ the defect-free and defective fabric image's projections onto the dual-dictionary as features for defect detection. Finally, the test results are determined by comparing the distance between the features to be measured. Experimental results reveal that the proposed algorithm is effective for patterned fabric defect detection and an acceptable average detection rate reaches by 94.2%.

  3. Shape Engineered Nanoparticle Fabrication for Biomedical Applications

    NASA Astrophysics Data System (ADS)

    Nasrullah, Azeem

    Semiconductor fabrication research has developed technologies that allow for the deposition and patterning of thin films, and can be applied to many different industries, including the field of medicine. One such application is the fabrication of nanoparticles. There is a wide variety of nanoparticle-based medical diagnostics and therapies, including drug delivery and cancer imaging. Most of the nanoparticles being studied are chemically synthesized and spherical in shape, and studies have shown that other shapes can be more useful in certain applications, especially those that involve in vivo analysis and treatment. Fabrication of particles using a tool set developed from the semiconductor industry can allow for a detailed study of size and shape dependence on nanoparticle uptake in the bloodstream. Particle fabrication is achieved using thin film deposition, ion beam proximity lithography, wet etching, and lift-off, all similar to techniques commonly found in the semiconductor industry. The particles are formed using patterns developed with proximity lithography, and this represents the largest effort in this work. An ion beam, generated by a saddle-field ion source, is used to irradiate a polymeric resist with a thin membrane stencil mask placed in close proximity to the resist coated substrate in order to define the pattern. A saddle-field ion source was constructed and characterized for proximity lithography, with a beam diameter of 4.8 mm for a +/-5% tolerance in current density, a source size range of 0.3--0.9 mm, an average brightness value of 15 nAcm2˙sr , and average exposure times of ≈30 s. Stencil masks were fabricated from silicon nitride membranes in order to generate the pattern for the nanoparticles, and the particles were fabricated using a bi-layer resist and a sacrificial copper layer for release into solution.

  4. Illustrating Surface Shape in Volume Data via Principal Direction-Driven 3D Line Integral Convolution

    NASA Technical Reports Server (NTRS)

    Interrante, Victoria

    1997-01-01

    The three-dimensional shape and relative depth of a smoothly curving layered transparent surface may be communicated particularly effectively when the surface is artistically enhanced with sparsely distributed opaque detail. This paper describes how the set of principal directions and principal curvatures specified by local geometric operators can be understood to define a natural 'flow' over the surface of an object, and can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape information in a perceptually intuitive way. The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures. By advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate a single scan-converted solid stroke texture that may intuitively represent the essential shape information of any level surface in the volume. To generate longer strokes over more highly curved areas, where the directional information is both most stable and most relevant, and to simultaneously downplay the visual impact of directional information in the flatter regions, one may dynamically redefine the length of the filter kernel according to the magnitude of the maximum principal curvature of the level surface at the point around which it is applied.

  5. Styrene-based shape memory foam: fabrication and mathematical modeling

    NASA Astrophysics Data System (ADS)

    Yao, Yongtao; Zhou, Tianyang; Qin, Chao; Liu, Yanju; Leng, Jinsong

    2016-10-01

    Shape memory polymer foam is a promising kind of structure in the biomedical and aerospace field. Shape memory styrene foam with uniform and controlled open-cell structure was successfully fabricated using a salt particulate leaching method. Shape recovery capability exists for foam programming in both high-temperature compression and low-temperature compression (Shape recovery properties such as shape fixing property and shape recovery ratio were also characterized. In order to provide guidance for the future fabrication of shape memory foam, the theories of Gibson and Ashby as well as differential micromechanics theory were applied to predict Young’s modulus and the mechanical behavior of SMP styrene foams during the compression process.

  6. Balance the nodule shape and surroundings: a new multichannel image based convolutional neural network scheme on lung nodule diagnosis

    NASA Astrophysics Data System (ADS)

    Sun, Wenqing; Zheng, Bin; Huang, Xia; Qian, Wei

    2017-03-01

    Deep learning is a trending promising method in medical image analysis area, but how to efficiently prepare the input image for the deep learning algorithms remains a challenge. In this paper, we introduced a novel artificial multichannel region of interest (ROI) generation procedure for convolutional neural networks (CNN). From LIDC database, we collected 54880 benign nodule samples and 59848 malignant nodule samples based on the radiologists' annotations. The proposed CNN consists of three pairs of convolutional layers and two fully connected layers. For each original ROI, two new ROIs were generated: one contains the segmented nodule which highlighted the nodule shape, and the other one contains the gradient of the original ROI which highlighted the textures. By combining the three channel images into a pseudo color ROI, the CNN was trained and tested on the new multichannel ROIs (multichannel ROI II). For the comparison, we generated another type of multichannel image by replacing the gradient image channel with a ROI contains whitened background region (multichannel ROI I). With the 5-fold cross validation evaluation method, the CNN using multichannel ROI II achieved the ROI based area under the curve (AUC) of 0.8823+/-0.0177, compared to the AUC of 0.8484+/-0.0204 generated by the original ROI. By calculating the average of ROI scores from one nodule, the lesion based AUC using multichannel ROI was 0.8793+/-0.0210. By comparing the convolved features maps from CNN using different types of ROIs, it can be noted that multichannel ROI II contains more accurate nodule shapes and surrounding textures.

  7. Fabrication of trough-shaped solar collectors

    DOEpatents

    Schertz, William W.

    1978-01-01

    There is provided a radiant energy concentration and collection device formed of a one-piece thin-walled plastic substrate including a plurality of nonimaging troughs with certain metallized surfaces of the substrate serving as reflective side walls for each trough. The one-piece plastic substrate is provided with a seating surface at the bottom of each trough which conforms to the shape of an energy receiver to be seated therein.

  8. Nanoparticles with tunable shape and composition fabricated by nanoimprint lithography

    NASA Astrophysics Data System (ADS)

    Alayo, Nerea; Conde-Rubio, Ana; Bausells, Joan; Borrisé, Xavier; Labarta, Amilcar; Batlle, Xavier; Pérez-Murano, Francesc

    2015-11-01

    Cone-like and empty cup-shaped nanoparticles of noble metals have been demonstrated to provide extraordinary optical properties for use as optical nanoanntenas or nanoresonators. However, their large-scale production is difficult via standard nanofabrication methods. We present a fabrication approach to achieve arrays of nanoparticles with tunable shape and composition by a combination of nanoimprint lithography, hard-mask definition and various forms of metal deposition. In particular, we have obtained arrays of empty cup-shaped Au nanoparticles showing an optical response with distinguishable features associated with the excitations of localized surface plasmons. Finally, this route avoids the most common drawbacks found in the fabrication of nanoparticles by conventional top-down methods, such as aspect ratio limitation, blurring, and low throughput, and it can be used to fabricate nanoparticles with heterogeneous composition.

  9. Optofluidic fabrication for 3D-shaped particles

    NASA Astrophysics Data System (ADS)

    Paulsen, Kevin S.; di Carlo, Dino; Chung, Aram J.

    2015-04-01

    Complex three-dimensional (3D)-shaped particles could play unique roles in biotechnology, structural mechanics and self-assembly. Current methods of fabricating 3D-shaped particles such as 3D printing, injection moulding or photolithography are limited because of low-resolution, low-throughput or complicated/expensive procedures. Here, we present a novel method called optofluidic fabrication for the generation of complex 3D-shaped polymer particles based on two coupled processes: inertial flow shaping and ultraviolet (UV) light polymerization. Pillars within fluidic platforms are used to deterministically deform photosensitive precursor fluid streams. The channels are then illuminated with patterned UV light to polymerize the photosensitive fluid, creating particles with multi-scale 3D geometries. The fundamental advantages of optofluidic fabrication include high-resolution, multi-scalability, dynamic tunability, simple operation and great potential for bulk fabrication with full automation. Through different combinations of pillar configurations, flow rates and UV light patterns, an infinite set of 3D-shaped particles is available, and a variety are demonstrated.

  10. Optofluidic fabrication for 3D-shaped particles.

    PubMed

    Paulsen, Kevin S; Di Carlo, Dino; Chung, Aram J

    2015-04-23

    Complex three-dimensional (3D)-shaped particles could play unique roles in biotechnology, structural mechanics and self-assembly. Current methods of fabricating 3D-shaped particles such as 3D printing, injection moulding or photolithography are limited because of low-resolution, low-throughput or complicated/expensive procedures. Here, we present a novel method called optofluidic fabrication for the generation of complex 3D-shaped polymer particles based on two coupled processes: inertial flow shaping and ultraviolet (UV) light polymerization. Pillars within fluidic platforms are used to deterministically deform photosensitive precursor fluid streams. The channels are then illuminated with patterned UV light to polymerize the photosensitive fluid, creating particles with multi-scale 3D geometries. The fundamental advantages of optofluidic fabrication include high-resolution, multi-scalability, dynamic tunability, simple operation and great potential for bulk fabrication with full automation. Through different combinations of pillar configurations, flow rates and UV light patterns, an infinite set of 3D-shaped particles is available, and a variety are demonstrated.

  11. Optofluidic fabrication for 3D-shaped particles

    PubMed Central

    Paulsen, Kevin S.; Di Carlo, Dino; Chung, Aram J.

    2015-01-01

    Complex three-dimensional (3D)-shaped particles could play unique roles in biotechnology, structural mechanics and self-assembly. Current methods of fabricating 3D-shaped particles such as 3D printing, injection moulding or photolithography are limited because of low-resolution, low-throughput or complicated/expensive procedures. Here, we present a novel method called optofluidic fabrication for the generation of complex 3D-shaped polymer particles based on two coupled processes: inertial flow shaping and ultraviolet (UV) light polymerization. Pillars within fluidic platforms are used to deterministically deform photosensitive precursor fluid streams. The channels are then illuminated with patterned UV light to polymerize the photosensitive fluid, creating particles with multi-scale 3D geometries. The fundamental advantages of optofluidic fabrication include high-resolution, multi-scalability, dynamic tunability, simple operation and great potential for bulk fabrication with full automation. Through different combinations of pillar configurations, flow rates and UV light patterns, an infinite set of 3D-shaped particles is available, and a variety are demonstrated. PMID:25904062

  12. Variations in size, shape and asymmetries of the third frontal convolution in hominids: paleoneurological implications for hominin evolution and the origin of language.

    PubMed

    Balzeau, Antoine; Gilissen, Emmanuel; Holloway, Ralph L; Prima, Sylvain; Grimaud-Hervé, Dominique

    2014-11-01

    The study of brain structural asymmetries as anatomical substrates of functional asymmetries in extant humans, great apes, and fossil hominins is of major importance in understanding the structural basis of modern human cognition. We propose methods to quantify the variation in size, shape and bilateral asymmetries of the third frontal convolution (or posterior inferior frontal gyrus) among recent modern humans, bonobos and chimpanzees, and fossil hominins using actual and virtual endocasts. These methodological improvements are necessary to extend previous qualitative studies of these features. We demonstrate both an absolute and relative bilateral increase in the size of the third frontal convolution in width and length between Pan species, as well as in hominins. We also observed a global bilateral increase in the size of the third frontal convolution across all species during hominin evolution, but also non-allometric intra-group variations independent of brain size within the fossil samples. Finally, our results show that the commonly accepted leftward asymmetry of Broca's cap is biased by qualitative observation of individual specimens. The trend during hominin evolution seems to be a reduction in size on the left compared with the right side, and also a clearer definition of the area. The third frontal convolution considered as a whole projects more laterally and antero-posteriorly in the right hemisphere. As a result, the left 'Broca's cap' looks more globular and better defined. Our results also suggest that the pattern of brain asymmetries is similar between Pan paniscus and hominins, leaving the gradient of the degree of asymmetry as the only relevant structural parameter. As the anatomical substrate related to brain asymmetry has been present since the appearance of the hominin lineage, it is not possible to prove a direct relationship between the extent of variations in the size, shape, and asymmetries of the third frontal convolution and the origin of

  13. Fabrication of a helical coil shape memory alloy actuator

    SciTech Connect

    O'Donnell, R.E.

    1992-02-01

    A fabrication process was developed to form, heat treat, and join NiTi shape memory alloy helical coils for use as mechanical actuators. Tooling and procedures were developed to wind both extension and compression-type coils on a manual lathe. Heat treating fixtures and techniques were used to set the memory'' of the NiTi alloy to the desired configuration. A swaging process was devised to fasten shape memory alloy extension coils to end fittings for use in actuator testing and for potential attachment to mechanical devices. The strength of this mechanical joint was evaluated.

  14. Fabrication of a helical coil shape memory alloy actuator

    SciTech Connect

    O`Donnell, R.E.

    1992-02-01

    A fabrication process was developed to form, heat treat, and join NiTi shape memory alloy helical coils for use as mechanical actuators. Tooling and procedures were developed to wind both extension and compression-type coils on a manual lathe. Heat treating fixtures and techniques were used to set the ``memory`` of the NiTi alloy to the desired configuration. A swaging process was devised to fasten shape memory alloy extension coils to end fittings for use in actuator testing and for potential attachment to mechanical devices. The strength of this mechanical joint was evaluated.

  15. Fabrication of a helical coil shape memory alloy actuator

    NASA Astrophysics Data System (ADS)

    Odonnell, R. E.

    1992-02-01

    A fabrication process was developed to form, heat treat, and join NiTi shape memory alloy helical coils for use as mechanical actuators. Tooling and procedures were developed to wind both extension and compression-type coils on a manual lathe. Heat treating fixtures and techniques were used to set the 'memory' of the NiTi alloy to the desired configuration. A swaging process was devised to fasten shape memory alloy extension coils to end fittings for use in actuator testing and for potential attachment to mechanical devices. The strength of this mechanical joint was evaluated.

  16. X-ray diffraction line profile analysis of nanostructured nickel oxide: Shape factor and convolution of crystallite size and microstrain contributions

    NASA Astrophysics Data System (ADS)

    Maniammal, K.; Madhu, G.; Biju, V.

    2017-01-01

    Nanostructured nickel oxide is synthesized through a chemical route and annealed at different temperatures. Contribution of crystallite size and microstrain to X-ray diffraction line broadening are analyzed by Williamson-Hall analysis using isotropic and anisotropic models. None of the models perform well in the case of samples with smaller average crystallite sizes. For sample with crystallite size 3 nm all models show negative slope which is physically meaningless. Analysis of shape factor shows that the line profiles are more Gaussian like. Size-strain plot method, which assumes a different convolution of the crystallite size and microstrain contributions, is found to be most suitable. The study highlights the fact that the convolution of crystallite size and microstrain contributions may differ for samples and should be taken into account while analyzing the observed line broadening. Microstrain values show a regular decrease with increase in the annealing temperature.

  17. EDITORIAL: Designer fabrication: nanotemplates get in shape Designer fabrication: nanotemplates get in shape

    NASA Astrophysics Data System (ADS)

    Demming, Anna

    2013-02-01

    People working in device design rarely see something that works without thinking how it could be made to work better. The work on anodic aluminum oxide materials in this issue provides a case in point [1]. Over the past century researchers have observed, manipulated and exploited the porous structures that result when anodizing aluminum in for example oxalic, sulfuric, and phosphoric acid solutions [1, 2]. The self-organized pore arrays have demonstrated the potential to facilitate high through-put, low-cost fabrication of nanocomposites as well as other nanostructures. The straight self-aligned nanochannels in porous anodic aluminum oxide (AAO) have long been accepted as an inherent property of these films and for many applications they are an attractive attribute. However, researchers in Taiwan have considered a novel manifestation of AAO materials which may enhance their natural attributes by generating arrays that bend [3]. Their work is an example of how even well studied systems continue to harbour surprises and scope for creative innovation. As the authors point out, 'This novel fan-out platform facilitates probing and handling many signals from different areas on a sample's surface and is therefore promising for applications in detection and manipulation at the nanoscale level'. It has long been recognized that the inter-pore distance, pore diameter and pore depth in AAO can be controlled by changing the anodization conditions. These accommodating features have motivated researchers to seek a better understanding of how to optimize fabrication conditions. A collaboration of researchers in Sweden, Chile and Uruguay studied the structural and optical properties of silver nanowires electrodeposited in commercially available nanoporous alumina templates, with a nominal pore diameter of 20 nm [4]. Their results revealed a decrease in the uniformity of pore filling with increasing deposition overpotential and suggested that overpotentials were preferred for the

  18. Fabrication and testing of SMA composite beam with shape control

    NASA Astrophysics Data System (ADS)

    Noolvi, Basavaraj; S, Raja; Nagaraj, Shanmukha; Mudradi, Varada Raj

    2017-07-01

    Smart materials are the advanced materials that have characteristics of sensing and actuation in response to the external stimuli like pressure, heat or electric charge etc. These materials can be integrated in to any structure to make it smart. From the different types of smart materials available, Shape Memory Alloy (SMA) is found to be more useful in designing new applications, which can offer more actuating speed, reduce the overall weight of the structure. The unique property of SMA is the ability to remember and recover from large strains of upto 8% without permanent deformation. Embedding the SMA wire/sheet in fiber-epoxy/flexible resin systems has many potential applications in Aerospace, Automobile, Medical, Robotics and various other fields. In this work the design, fabrication, and testing of smart SMA composite beam has been carried out. Two types of epoxy based resin systems namely LY 5210 resin system and EPOLAM 2063 resin system are used in fabricating the SMA composite specimens. An appropriate mould is designed and fabricated to retain the pre-strain of SMA wire during high temperature post curing of composite specimens. The specimens are fabricated using vacuum bag technique.

  19. Fabrication and modeling of shape memory alloy springs

    NASA Astrophysics Data System (ADS)

    Heidari, B.; Kadkhodaei, M.; Barati, M.; Karimzadeh, F.

    2016-12-01

    In this paper, shape memory alloy (SMA) helical springs are produced by shape setting two sets of NiTi (Ti-55.87 at% Ni) wires, one of which showing shape memory effect and another one showing pseudoelasticity at the ambient temperature. Different pitches as well as annealing temperatures are tried to investigate the effect of such parameters on the thermomechanical characteristics of the fabricated springs. Phase transformation temperatures of the products are measured by differential scanning calorimetry and are compared with those of the original wires. Compression tests are also carried out, and stiffness of each spring is determined. The desired pitches are so that a group of springs experiences phase transition during loading while the other does not. The former shows a varying stiffness upon the application of compression, but the latter acts as passive springs with a predetermined stiffness. Based on the von-Mises effective stress and strain, an enhanced one-dimensional constitutive model is further proposed to describe the shear stress-strain response within the coils of an SMA spring. The theoretically predicted force-displacement responses of the produced springs are shown to be in a reasonable agreement with the experimental results. Finally, effects of variations in geometric parameters on the axial force-displacement response of an SMA spring are investigated.

  20. Thermocapillary Technique for Shaping and Fabricating Optical Ribbon Waveguides

    NASA Astrophysics Data System (ADS)

    Fiedler, Kevin; Troian, Sandra

    The demand for ever increasing bandwidth and higher speed communication has ushered the next generation optoelectronic integrated circuits which directly incorporate polymer optical waveguide devices. Polymer melts are very versatile materials which have been successfully cast into planar single- and multimode waveguides using techniques such as embossing, photolithography and direct laser writing. In this talk, we describe a novel thermocapillary patterning method for fabricating waveguides in which the free surface of an ultrathin molten polymer film is exposed to a spatially inhomogeneous temperature field via thermal conduction from a nearby cooled mask pattern held in close proximity. The ensuring surface temperature distribution is purposely designed to pool liquid selectively into ribbon shapes suitable for optical waveguiding, but with rounded and not rectangular cross sectional areas due to capillary forces. The solidified waveguide patterns which result from this non-contact one step procedure exhibit ultrasmooth interfaces suitable for demanding optoelectronic applications. To complement these studies, we have also conducted finite element simulations for quantifying the influence of non-rectangular cross-sectional shapes on mode propagation and losses. Kf gratefully acknowledges support from a NASA Space Technology Research Fellowship.

  1. Compressed convolution

    NASA Astrophysics Data System (ADS)

    Elsner, Franz; Wandelt, Benjamin D.

    2014-01-01

    We introduce the concept of compressed convolution, a technique to convolve a given data set with a large number of non-orthogonal kernels. In typical applications our technique drastically reduces the effective number of computations. The new method is applicable to convolutions with symmetric and asymmetric kernels and can be easily controlled for an optimal trade-off between speed and accuracy. It is based on linear compression of the collection of kernels into a small number of coefficients in an optimal eigenbasis. The final result can then be decompressed in constant time for each desired convolved output. The method is fully general and suitable for a wide variety of problems. We give explicit examples in the context of simulation challenges for upcoming multi-kilo-detector cosmic microwave background (CMB) missions. For a CMB experiment with detectors with similar beam properties, we demonstrate that the algorithm can decrease the costs of beam convolution by two to three orders of magnitude with negligible loss of accuracy. Likewise, it has the potential to allow the reduction of disk space required to store signal simulations by a similar amount. Applications in other areas of astrophysics and beyond are optimal searches for a large number of templates in noisy data, e.g. from a parametrized family of gravitational wave templates; or calculating convolutions with highly overcomplete wavelet dictionaries, e.g. in methods designed to uncover sparse signal representations.

  2. On the shape and fabric of human history

    PubMed Central

    Gray, Russell D.; Bryant, David; Greenhill, Simon J.

    2010-01-01

    In this paper we outline two debates about the nature of human cultural history. The first focuses on the extent to which human history is tree-like (its shape), and the second on the unity of that history (its fabric). Proponents of cultural phylogenetics are often accused of assuming that human history has been both highly tree-like and consisting of tightly linked lineages. Critics have pointed out obvious exceptions to these assumptions. Instead of a priori dichotomous disputes about the validity of cultural phylogenetics, we suggest that the debate is better conceptualized as involving positions along continuous dimensions. The challenge for empirical research is, therefore, to determine where particular aspects of culture lie on these dimensions. We discuss the ability of current computational methods derived from evolutionary biology to address these questions. These methods are then used to compare the extent to which lexical evolution is tree-like in different parts of the world and to evaluate the coherence of cultural and linguistic lineages. PMID:21041216

  3. Fabrication of Adhesive Lenses Using Free Surface Shaping

    NASA Astrophysics Data System (ADS)

    Hoheisel, D.; Kelb, C.; Wall, M.; Roth, B.; Rissing, L.

    2013-09-01

    Two approaches for fabricating polymer lenses are presented in this paper. Both are based on filling circular holes with UV curing adhesives. Initially, the viscous adhesive material creates a liquid and spherical free surface due to its own surface tension. This shape is then preserved by curing with UV-hardening light. For the first approach, the holes are generated in a 4 inch Si-wafer by deep reactive ion etching (DRIE) and for the second, a polydimethylsiloxane (PDMS) mould is manufactured. Three types of UV-curing adhesives are investigated (NOA 61, NOA 88 and NEA 121 by Norland Products). Preliminary to the determination of the lens curvature, a contact angle goniometer is used for taking side view images of the lenses. The radius of curvature is then extracted via image processing with the software MATLAB®. Furthermore, the surface roughness of the PDMS mould and the generated lenses is measured with a white light interferometer to characterize the casting process. The resolution power of the generated lenses is evaluated by measurement of their point spread functions (psf) and modulation transfer functions (mtf), respectively.

  4. Fabrication of silicon-based shape memory alloy micro-actuators

    NASA Technical Reports Server (NTRS)

    Johnson, A. David; Busch, John D.; Ray, Curtis A.; Sloan, Charles L.

    1992-01-01

    Thin film shape memory alloy has been integrated with silicon in a new actuation mechanism for microelectromechanical systems. This paper compares nickel-titanium film with other actuators, describes recent results of chemical milling processes developed to fabricate shape memory alloy microactuators in silicon, and describes simple actuation mechanisms which have been fabricated and tested.

  5. Fabrication of micro DOE using micro tools shaped with focused ion beam.

    PubMed

    Xu, Z W; Fang, F Z; Zhang, S J; Zhang, X D; Hu, X T; Fu, Y Q; Li, L

    2010-04-12

    A novel method is proposed to fabricate micro Diffractive Optical Elements (DOE) using micro cutting tools shaped with focused ion beam (FIB) milling. Micro tools with nanometric cutting edges and complicated shapes are fabricated by controlling the tool facet's orientation relative to the FIB. The tool edge radius of less than 30 nm is achieved for the nano removal of the work materials. Semi-circular micro tools and DOE-shaped micro tools are developed to fabricate micro-DOE and sinusoidal modulation templates. Experiments show that the proposed method can be a high efficient way in fabricating micro-DOE with nanoscale surface finishes.

  6. Fabrication of shape memory nanofibers by electrospinning method

    NASA Astrophysics Data System (ADS)

    Zhang, Fenghua; Zhang, Zhichun; Liu, Yanju; Leng, Jinsong

    2013-04-01

    Shape memory nanofibers are capable of fixing a temporary shape and recovering a permanent shape in response to stimulus. Nafion nanofibers with shape memory effect are achieved via electrospinning technology. The resulting nanofibres exhibit the smooth, continuous, uniform fibrous structure. The diameter of nanofibers increases after annealing progress at different temperatures. The shape memory effect is evaluated in a fixed force controlled tensile test. Electrospun Nafion nanofibers show excellent shape memory properties upon heat. The shape fixity rates and shape recovery rates are about 95-96% and 87-89% after consecutive three shape memory cycles, respectively. The structure of electrospun nanofibers is stable and reversible for at least three cycles of shape memory tests. These results indicate that shape memory Nafion nanofibers can be used in a wide potential application fields such as smart materials and structures in the future.

  7. Finite element modeling and fabrication of an SMA-SMP shape memory composite actuator

    NASA Astrophysics Data System (ADS)

    Souri, Mohammad

    Shape memory alloys and polymers have been extensively researched recently because of their unique ability to recover large deformations. Shape memory polymers (SMPs) are able to recover large deformations compared to shape memory alloys (SMAs), although SMAs have higher strength and are able to generate more stress during recovery. This project focuses on procedure for fabrication and Finite Element Modeling (FEM) of a shape memory composite actuator. First, SMP was characterized to reveal its mechanical properties. Specifically, glass transition temperature, the effects of temperature and strain rate on compressive response and recovery properties of shape memory polymer were studied. Then, shape memory properties of a NiTi wire, including transformation temperatures and stress generation, were investigated. SMC actuator was fabricated by using epoxy based SMP and NiTi SMA wire. Experimental tests confirmed the reversible behavior of fabricated shape memory composites. (Abstract shortened by ProQuest.).

  8. Method for fabricating uranium alloy articles without shape memory effects

    DOEpatents

    Banker, John G.

    1985-01-01

    Uranium-rich niobium and niobium-zirconium alloys possess a characteristic known as shape memory effect wherein shaped articles of these alloys recover their original shape when heated. The present invention circumvents this memory behavior by forming the alloys into the desired configuration at elevated temperatures with "cold" matched dies and maintaining the shaped articles between the dies until the articles cool to ambient temperature.

  9. Method for fabricating uranium alloy articles without shape memory effects

    DOEpatents

    Banker, J.G.

    1980-05-21

    Uranium-rich niobium and niobium-zirconium alloys possess a characteristic known as shape memory effect wherein shaped articles of these alloys recover their original shape when heated. The present invention circumvents this memory behavior by forming the alloys into the desired configuration at elevated temperatures with cold matched dies and maintaining the shaped articles between the dies until the articles cool to ambient temperature.

  10. Adjustable reed for weaving net-shaped tailored fabrics

    NASA Technical Reports Server (NTRS)

    Farley, Gary L. (Inventor)

    1995-01-01

    An apparatus and method for forming woven fabrics through the use of an adjustable reed. The adjustable reed has multiple groups of reed wires that guide the warp yarns. The groups of reed wires move on reed rails parallel to the warp direction. In addition, rail expanders permit the space between the reed wires to be modified and telescoping rods attached to the rail sliders can be turned to permit the reed wires to be skewed to alter the fill yarn angle. These adjustments to the reed permit simultaneous variation of fill yarn angles and fabric widths and allow these variations to be made during fabrication, without the need to halt production.

  11. Fabrication of porous NiTi shape memory alloy structures using laser engineered net shaping.

    PubMed

    Krishna, B Vamsi; Bose, Susmita; Bandyopadhyay, Amit

    2009-05-01

    Porous NiTi alloy samples were fabricated with 12-36% porosity from equiatomic NiTi alloy powder using laser engineered net shaping (LENS). The effects of processing parameters on density and properties of laser-processed NiTi alloy samples were investigated. It was found that the density increased rapidly with increasing the specific energy input up to 50 J/mm(3). Further increase in the energy input had small effect on density. High cooling rates associated with LENS processing resulted in higher amount of cubic B2 phase, and increased the reverse transformation temperatures of porous NiTi samples due to thermally induced stresses and defects. Transformation temperatures were found to be independent of pore volume, though higher pore volume in the samples decreased the maximum recoverable strain from 6% to 4%. Porous NiTi alloy samples with 12-36% porosity exhibited low Young's modulus between 2 and 18 GPa as well as high compressive strength and recoverable strain. Because of high open pore volume between 36% and 62% of total volume fraction porosity, these porous NiTi alloy samples can potentially accelerate the healing process and improve biological fixation when implanted in vivo. Thus porous NiTi is a promising biomaterial for hard tissue replacements.

  12. Adjustable reed for weaving net-shaped tailored fabrics

    NASA Technical Reports Server (NTRS)

    Farley, Gary L. (Inventor)

    1994-01-01

    The invention is an apparatus and method for forming woven fabrics through the use of an adjustable reed. The adjustable reed has multiple groups of reed wires that guide the warp yarns. The groups of reed wires move on reed rails parallel to the warp direction. In addition, rail expanders permit the space between the reed wires to be modified and telescoping rods attached to the rail sliders can be turned to permit the reed wires to be skewed to alter the fill yarn angle. These adjustments to the reed permit simultaneous variation of fill yarn angles and fabric widths and allow these variations to be made during fabrication, without the need to halt production.

  13. Adjustable reed for weaving net-shaped tailored fabrics

    NASA Astrophysics Data System (ADS)

    Farley, Gary L.

    1994-06-01

    The invention is an apparatus and method for forming woven fabrics through the use of an adjustable reed. The adjustable reed has multiple groups of reed wires that guide the warp yarns. The groups of reed wires move on reed rails parallel to the warp direction. In addition, rail expanders permit the space between the reed wires to be modified and telescoping rods attached to the rail sliders can be turned to permit the reed wires to be skewed to alter the fill yarn angle. These adjustments to the reed permit simultaneous variation of fill yarn angles and fabric widths and allow these variations to be made during fabrication, without the need to halt production.

  14. Strategic design and fabrication of acrylic shape memory polymers

    NASA Astrophysics Data System (ADS)

    Park, Ju Hyuk; Kim, Hansu; Ryoun Youn, Jae; Song, Young Seok

    2017-08-01

    Modulation of thermomechanics nature is a critical issue for an optimized use of shape memory polymers (SMPs). In this study, a strategic approach was proposed to control the transition temperature of SMPs. Free radical vinyl polymerization was employed for tailoring and preparing acrylic SMPs. Transition temperatures of the shape memory tri-copolymers were tuned by changing the composition of monomers. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy analyses were carried out to evaluate the chemical structures and compositions of the synthesized SMPs. The thermomechanical properties and shape memory performance of the SMPs were also examined by performing dynamic mechanical thermal analysis. Numerical simulation based on a finite element method provided consistent results with experimental cyclic shape memory tests of the specimens. Transient shape recovery tests were conducted and optical transparence of the samples was identified. We envision that the materials proposed in this study can help develop a new type of shape-memory devices in biomedical and aerospace engineering applications.

  15. Method for fabrication of cylindrical microlenses of selected shape

    DOEpatents

    Snyder, J.J.; Baer, T.M.

    1992-01-14

    The present invention provides a diffraction limited, high numerical aperture (fast) cylindrical microlens. The method for making the microlens is adaptable to produce a cylindrical lens that has almost any shape on its optical surfaces. The cylindrical lens may have a shape, such as elliptical or hyperbolic, designed to transform some particular given input light distribution into some desired output light distribution. In the method, the desired shape is first formed in a glass preform. Then, the preform is heated to the minimum drawing temperature and a fiber is drawn from it. The cross-sectional shape of the fiber bears a direct relation to the shape of the preform from which it was drawn. During the drawing process, the surfaces become optically smooth due to fire polishing. The present invention has many applications, such as integrated optics, optical detectors and laser diodes. The lens, when connected to a laser diode bar, can provide a high intensity source of laser radiation for pumping a high average power solid state laser. In integrated optics, a lens can be used to couple light into and out of apertures such as waveguides. The lens can also be used to collect light, and focus it on a detector. 11 figs.

  16. Method for fabrication of cylindrical microlenses of selected shape

    DOEpatents

    Snyder, James J.; Baer, Thomas M.

    1992-01-01

    The present invention provides a diffraction limited, high numerical aperture (fast) cylindrical microlens. The method for making the microlens is adaptable to produce a cylindrical lens that has almost any shape on its optical surfaces. The cylindrical lens may have a shape, such as elliptical or hyperbolic, designed to transform some particular given input light distribution into some desired output light distribution. In the method, the desired shape is first formed in a glass preform. Then, the preform is heated to the minimum drawing temperature and a fiber is drawn from it. The cross-sectional shape of the fiber bears a direct relation to the shape of the preform from which it was drawn. During the drawing process, the surfaces become optically smooth due to fire polishing. The present invention has many applications, such as integrated optics, optical detectors and laser diodes. The lens, when connected to a laser diode bar, can provide a high intensity source of laser radiation for pumping a high average power solid state laser. In integrated optics, a lens can be used to couple light into and out of apertures such as waveguides. The lens can also be used to collect light, and focus it on a detector.

  17. Method for fabrication of cylindrical microlenses of selected shape

    DOEpatents

    Snyder, James J.; Baer, Thomas M.

    1992-01-01

    The present invention provides a diffraction limited, high numerical aperture (fast) cylindrical microlens. The method for making the microlens is adaptable to produce a cylindrical lens that has almost any shape on its optical surfaces. The cylindrical lens may have a shape, such as elliptical or hyperbolic, designed to transform some particular given input light distribution into some desired output light distribution. In the method, the desired shape is first formed in a glass preform. Then, the preform is heated to the minimum drawing temperature and a fiber is drawn from it. The cross-sectional shape of the fiber bears a direct relation to the shape of the preform from which it was drawn. During the drawing process, the surfaces become optically smooth due to fire polishing. The present invention has many applications, such as integrated optics, optical detectors and laser diodes. The lens, when connected to a laser diode bar, can provide a high intensity source of laser radiation for pumping a high average power solid state laser. In integrated optics, a lens can be used to couple light into and out of apertures such as waveguides. The lens can also be used to collect light, and focus it on a detector.

  18. Progress in net shape fabrication of alpha sic turbine components

    NASA Technical Reports Server (NTRS)

    Sweeting, T. B.; Frechette, F. J.; Macbeth, J. W.

    1984-01-01

    An update of the status of ceramic component development of the AGT Programs is presented. Activity on AGTO Program focussed on the following: successful transition from the prototype to engine configuration rotor, investigation of alternate rotor molding techniques, and completion of scroll assemblies. Progress on the Garrett AGT Program was highlighted by the introduction of plastic molding and extrusion to parts which were previously fabricated by slip casting and isopressing respectively.

  19. Progress in net shape fabrication of alpha sic turbine components

    NASA Technical Reports Server (NTRS)

    Sweeting, T. B.; Frechette, F. J.; Macbeth, J. W.

    1984-01-01

    An update of the status of ceramic component development of the AGT Programs is presented. Activity on AGTO Program focussed on the following: successful transition from the prototype to engine configuration rotor, investigation of alternate rotor molding techniques, and completion of scroll assemblies. Progress on the Garrett AGT Program was highlighted by the introduction of plastic molding and extrusion to parts which were previously fabricated by slip casting and isopressing respectively.

  20. Design and fabrication of an E-shaped wearable textile antenna on PVB-coated hydrophobic polyester fabric

    NASA Astrophysics Data System (ADS)

    Babu Roshni, Satheesh; Jayakrishnan, M. P.; Mohanan, P.; Peethambharan Surendran, Kuzhichalil

    2017-10-01

    In this paper, we investigated the simulation and fabrication of an E-shaped microstrip patch antenna realized on multilayered polyester fabric suitable for WiMAX (Worldwide Interoperability for Microwave Access) applications. The main challenges while designing a textile antenna were to provide adequate thickness, surface uniformity and water wettability to the textile substrate. Here, three layers of polyester fabric were stacked together in order to obtain sufficient thickness, and were subsequently dip coated with polyvinyl butyral (PVB) solution. The PVB-coated polyester fabric showed a hydrophobic nature with a contact angle of 91°. The RMS roughness of the uncoated and PVB-coated polyester fabric was about 341 nm and 15 nm respectively. The promising properties, such as their flexibility, light weight and cost effectiveness, enable effortless integration of the proposed antenna into clothes like polyester jackets. Simulated and measured results in terms of return loss as well as gain were showcased to confirm the usefulness of the fabricated prototype. The fabricated antenna successfully operates at 3.37 GHz with a return loss of 21 dB and a maximum measured gain of 3.6 dB.

  1. Near net shape processing for solar thermal propulsion hardware using directed light fabrication

    SciTech Connect

    Milewski, J.O.; Fonseca, J.C.; Lewis, G.K.

    1998-12-01

    Directed light fabrication (DLF) is a direct metal deposition process that fuses gas delivered powder, in the focal zone of a high powered laser beam to form fully fused near net shaped components. The near net shape processing of rhenium, tungsten, iridium and other high temperature materials may offer significant cost savings compared with conventional processing. This paper describes a 3D parametric solid model, integrated with a manufacturing model, and creating a control field which runs on the DLF machine directly depositing a fully dense, solid metal, near net shaped, nozzle component. Examples of DLF deposited rhenium, iridium and tantalum, from previous work, show a continuously solidified microstructure in rod and tube shapes. Entrapped porosity indicates the required direction for continued process development. These combined results demonstrate the potential for a new method to fabricate complex near net shaped components using materials of interest to the space and aerospace industries.

  2. Method of forming variable cross-sectional shaped three-dimensional fabrics

    NASA Technical Reports Server (NTRS)

    Mohamed, Mansour H. (Inventor); Zhang, Zhong-Huai (Inventor)

    1992-01-01

    Method of weaving a variable cross-sectional shaped three-dimensional fabric which utilizes different weft yarn insertion from at least one side of the warp layers for selectively inserting weft yarns into different portions of the fabric cross-sectional profile defined by the warp yarn layers during the weaving process. If inserted from both sides of the warp yarn layers, the weft yarns may be inserted simultaneously or alternately from each side of the warp yarn layers. The vertical yarn is then inserted into the fabric by reciprocation of a plurality of harnesses which separate the vertical yarn into a plurality of vertical yarn systems as required by the shape of the three-dimensional fabric being formed.

  3. Scalable, Shape-specific, Top-down Fabrication Methods for the Synthesis of Engineered Colloidal Particles

    PubMed Central

    Merkel, Timothy J.; Herlihy, Kevin P.; Nunes, Janine; Orgel, Ryan M.; Rolland, Jason P.; DeSimone, Joseph M.

    2010-01-01

    The search for a method to fabricate non-spherical colloidal particles from a variety of materials is of growing interest. As the commercialization of nanotechnology continues to expand, the ability to translate particle fabrication methods from a laboratory to an industrial scale is of increasing significance. In this article, we examine several of the most readily scalable top-down methods for the fabrication of such shape specific particles and compare their capabilities with respect to particle composition, size, shape and complexity as well as the scalability of the method. We offer an extensive examination of Particle Replication In Non-wetting Templates (PRINT®) with regards to the versatility and scalability of this technique. We also detail the specific methods used in PRINT particle fabrication, including harvesting, purification and surface modification techniques, with examination of both past and current methods. PMID:20000620

  4. Convolution of Two Series

    ERIC Educational Resources Information Center

    Umar, A.; Yusau, B.; Ghandi, B. M.

    2007-01-01

    In this note, we introduce and discuss convolutions of two series. The idea is simple and can be introduced to higher secondary school classes, and has the potential of providing a good background for the well known convolution of function.

  5. Convolution in Convolution for Network in Network.

    PubMed

    Pang, Yanwei; Sun, Manli; Jiang, Xiaoheng; Li, Xuelong

    2017-03-16

    Network in network (NiN) is an effective instance and an important extension of deep convolutional neural network consisting of alternating convolutional layers and pooling layers. Instead of using a linear filter for convolution, NiN utilizes shallow multilayer perceptron (MLP), a nonlinear function, to replace the linear filter. Because of the powerfulness of MLP and 1 x 1 convolutions in spatial domain, NiN has stronger ability of feature representation and hence results in better recognition performance. However, MLP itself consists of fully connected layers that give rise to a large number of parameters. In this paper, we propose to replace dense shallow MLP with sparse shallow MLP. One or more layers of the sparse shallow MLP are sparely connected in the channel dimension or channel-spatial domain. The proposed method is implemented by applying unshared convolution across the channel dimension and applying shared convolution across the spatial dimension in some computational layers. The proposed method is called convolution in convolution (CiC). The experimental results on the CIFAR10 data set, augmented CIFAR10 data set, and CIFAR100 data set demonstrate the effectiveness of the proposed CiC method.

  6. Distal Convoluted Tubule

    PubMed Central

    Ellison, David H.

    2014-01-01

    The distal convoluted tubule is the nephron segment that lies immediately downstream of the macula densa. Although short in length, the distal convoluted tubule plays a critical role in sodium, potassium, and divalent cation homeostasis. Recent genetic and physiologic studies have greatly expanded our understanding of how the distal convoluted tubule regulates these processes at the molecular level. This article provides an update on the distal convoluted tubule, highlighting concepts and pathophysiology relevant to clinical practice. PMID:24855283

  7. Understanding the microstructure and properties of components fabricated by laser engineered net shaping (LENS)

    SciTech Connect

    GRIFFITH,MICHELLE L.; ENSZ,MARK T.; PUSKAR,JOSEPH D.; ROBINO,CHARLES V.; BROOKS,JOHN A.; PHILLIBER,JOEL A.; SMUGERESKY,JOHN E.; HOFMEISTER,W.H.

    2000-05-18

    Laser Engineered Net Shaping (LENS) is a novel manufacturing process for fabricating metal parts directly from Computer Aided Design (CAD) solid models. The process is similar to rapid prototyping technologies in its approach to fabricate a solid component by layer additive methods. However, the LENS technology is unique in that fully dense metal components with material properties that are similar to that of wrought materials can be fabricated. The LENS process has the potential to dramatically reduce the time and cost required realizing functional metal parts. In addition, the process can fabricate complex internal features not possible using existing manufacturing processes. The real promise of the technology is the potential to manipulate the material fabrication and properties through precision deposition of the material, which includes thermal behavior control, layered or graded deposition of multi-materials, and process parameter selection. This paper describes the authors' research to understand solidification aspects, thermal behavior, and material properties for laser metal deposition technologies.

  8. Fabrication and Characterization of Carbon Nanofiber Reinforced Shape Memory Epoxy (CNFR-SME) Composites

    NASA Astrophysics Data System (ADS)

    Wang, Jiuyang

    Shape memory polymers have a wide range of applications due to their ability to mechanically change shapes upon external stimulus, while their achievable composite counterparts prove even more versatile. An overview of literature on shape memory materials, fillers and composites was provided to pave a foundation for the materials used in the current study and their inherent benefits. This study details carbon nanofiber and composite fabrication and contrasts their material properties. In the first section, the morphology and surface chemistry of electrospun-poly(acrylonitrile)-based carbon nanofiber webs were tailored through various fabrication methods and impregnated with a shape memory epoxy. The morphologies, chemical compositions, thermal stabilities and electrical resistivities of the carbon nanofibers and composites were then characterized. In the second section, an overview of thermal, mechanical and shape memory characterization techniques for shape memory polymers and their composites was provided. Thermal and mechanical properties in addition to the kinetic and dynamic shape memory performances of neat epoxy and carbon nanofiber/epoxy composites were characterized. The various carbon nanofiber web modifications proved to have notable influence on their respective composite performances. The results from these two sections lead to an enhanced understanding of these carbon nanofiber reinforced shape memory epoxy composites and provided insight for future studies to tune these composites at will.

  9. Free form fabrication of metallic components using laser engineered net shaping (LENS{trademark})

    SciTech Connect

    Griffith, M.L.; Keicher, D.M.; Atwood, C.L.

    1996-09-01

    Solid free form fabrication is one of the fastest growing automated manufacturing technologies that has significantly impacted the length of time between initial concept and actual part fabrication. Starting with CAD renditions of new components, several techniques such as stereolithography and selective laser sintering are being used to fabricate highly accurate complex three-dimensional concept models using polymeric materials. Coupled with investment casting techniques, sacrificial polymeric objects are used to minimize costs and time to fabricate tooling used to make complex metal castings. This paper will describe recent developments in a new technology, known as LENS{sup {trademark}} (Laser Engineered Net Shaping), to fabricate metal components directly from CAD solid models and thus further reduce the lead times for metal part fabrication. In a manner analogous to stereolithography or selective sintering, the LENS{sup {trademark}} process builds metal parts line by line and layer by layer. Metal particles are injected into a laser beam, where they are melted and deposited onto a substrate as a miniature weld pool. The trace of the laser beam on the substrate is driven by the definition of CAD models until the desired net-shaped densified metal component is produced.

  10. Fabrication and characterization of an egg-shaped hollow fiber microbubble

    NASA Astrophysics Data System (ADS)

    Wang, Guanjun; Ruan, Yinlan; Jia, Pinggang; Gui, Zhiguo; Zhang, Pengcheng; Wang, Chao; Liu, Shen; Liao, Changrui; Yin, Guolu; Wang, Yiping

    2017-04-01

    In this paper, an egg-shaped microbubble is proposed and analyzed firstly, which is fabricated by the pressure-assisted arc discharge technique. By tailoring the arc parameters and the position of glass tube during the fabrication process, the thinnest wall of the fabricated microbubble could reach to the level of 873nm. Then, the fiber Fabry-Perot interference technique is used to analyze the deformation of microbubble that under different filling pressures. It is found that the endface of micro-bubble occurs compression when the inner pressure increasing from 4Kpa to 1400KPa. And the pressure sensitivity of such egg-shaped microbubble sample is14.3pm/Kpa. Results of this study could be good reference for developing new pressure sensors, etc.

  11. Fabrication and Testing of a Leading-Edge-Shaped Heat Pipe

    NASA Technical Reports Server (NTRS)

    Glass, David E.; Merrigan, Michael A.; Sena, J. Tom; Reid, Robert S.

    1998-01-01

    The development of a refractory-composite/heat-pipe-cooled leading edge has evolved from the design stage to the fabrication and testing of a full size, leading-edge-shaped heat pipe. The heat pipe had a 'D-shaped' cross section and was fabricated from arc cast Mo-4lRe. An artery was included in the wick. Several issues were resolved with the fabrication of the sharp leading edge radius heat pipe. The heat pipe was tested in a vacuum chamber at Los Alamos National Laboratory using induction heating and was started up from the frozen state several times. However, design temperatures and heat fluxes were not obtained due to premature failure of the heat pipe resulting from electrical discharge between the induction heating apparatus and the heat pipe. Though a testing anomaly caused premature failure of the heat pipe, successful startup and operation of the heat pipe was demonstrated.

  12. Rapid fabrication of cylindrical microlens array by shaped femtosecond laser direct writing

    NASA Astrophysics Data System (ADS)

    Luo, Zhi; Wang, Cong; Yin, Kai; Dong, Xinran; Chu, Dongkai; Duan, Ji'an

    2016-07-01

    In this study, a remarkable spatial shaping approach is proposed to transform Gaussian femtosecond laser into quasi-Bessel optical field with compressed central lobe and amplified side lobes of the spatial intensity profile. Based on this technique, inward bulge trench (IBT) structures are fabricated with high efficiency on the surface of PMMA by a single illumination step, whose cross-sectional profile is opposite to the results fabricated by Gaussian beam. And plano-convex cylindrical microlens array, which is consistent in size and shape throughout a large sample area, is formed through simply piecing together the IBT structures during fabricating process. Furthermore, numerical simulations of optical field in radial direction and on-axial direction are exploited to rationalize the dependence of the patterned microstructures on the spatial intensity distribution of femtosecond laser.

  13. Laser Spray Fabrication for Net-Shape Rapid Product Realization LDRD

    SciTech Connect

    Atwood, C.L.; Ensz, M.T.; Greene, D.L.; Griffith, M.L.; Harwell, L.D.; Jeantette, F.P.; Keicher, D.M.; Oliver, M.S.; Reckaway, D.E.; Romero, J.A.; Schlienger, M.E.; Smugeresky, J.D.

    1999-04-01

    The primary purpose of this LDRD project was to characterize the laser deposition process and determine the feasibility of fabricating complex near-net shapes directly from a CAD solid model. Process characterization provided direction in developing a system to fabricate complex shapes directly from a CAD solid model. Our goal for this LDRD was to develop a system that is robust and provides a significant advancement to existing technologies (e.g., polymeric-based rapid prototyping, laser welding). Development of the process will allow design engineers to produce functional models of their designs directly from CAD files. The turnaround time for complex geometrical shaped parts will be hours instead of days and days instead of months. With reduced turnaround time, more time can be spent on the product-design phase to ensure that the best component design is achieved. Maturation of this technology will revolutionize the way the world produces structural components.

  14. Fabrication method for cores of structural sandwich materials including star shaped core cells

    DOEpatents

    Christensen, Richard M.

    1997-01-01

    A method for fabricating structural sandwich materials having a core pattern which utilizes star and non-star shaped cells. The sheets of material are bonded together or a single folded sheet is used, and bonded or welded at specific locations, into a flat configuration, and are then mechanically pulled or expanded normal to the plane of the sheets which expand to form the cells. This method can be utilized to fabricate other geometric cell arrangements than the star/non-star shaped cells. Four sheets of material (either a pair of bonded sheets or a single folded sheet) are bonded so as to define an area therebetween, which forms the star shaped cell when expanded.

  15. Fabrication method for cores of structural sandwich materials including star shaped core cells

    DOEpatents

    Christensen, R.M.

    1997-07-15

    A method for fabricating structural sandwich materials having a core pattern which utilizes star and non-star shaped cells is disclosed. The sheets of material are bonded together or a single folded sheet is used, and bonded or welded at specific locations, into a flat configuration, and are then mechanically pulled or expanded normal to the plane of the sheets which expand to form the cells. This method can be utilized to fabricate other geometric cell arrangements than the star/non-star shaped cells. Four sheets of material (either a pair of bonded sheets or a single folded sheet) are bonded so as to define an area therebetween, which forms the star shaped cell when expanded. 3 figs.

  16. Multiplex lateral-flow test strips fabricated by two-dimensional shaping.

    PubMed

    Fenton, Erin M; Mascarenas, Monica R; López, Gabriel P; Sibbett, Scott S

    2009-01-01

    We have fabricated paper- and nitrocellulose-based lateral-flow devices that are shaped in two dimensions by a computer-controlled knife. The resulting star, candelabra, and other structures are spotted with multiple bioassay reagents to produce multiplex lateral-flow assays. We have also fabricated laminar composites in which porous nitrocellulose media are sandwiched between vinyl and polyester plastic films. This minimizes evaporation, protects assay surfaces from contamination and dehydration, and eliminates the need for the conventional hard plastic cassette holders that are typically used to package commercial lateral-flow diagnostic strips. The reported fabrication method is novel, low-cost, and well-suited to (i) fabrication and adoption in resource-poor areas, (ii) prototype development, (iii) high-volume manufacturing, and (iii) improving rates of operator error.

  17. Powder-Coated Towpreg: Avenues to Near Net Shape Fabrication of High Performance Composites

    NASA Technical Reports Server (NTRS)

    Johnston, N. J.; Cano, R. J.; Marchello, J. M.; Sandusky, D. A.

    1995-01-01

    Near net shape parts were fabricated from powder-coated preforms. Key issues including powder loss during weaving and tow/tow friction during braiding were addressed, respectively, by fusing the powder to the fiber prior to weaving and applying a water-based gel to the towpreg prior to braiding. A 4:1 debulking of a complex 3-D woven powder-coated preform was achieved in a single step utilizing expansion rubber molding. Also, a process was developed for using powder-coated towpreg to fabricate consolidated ribbon having good dimensional integrity and low voids. Such ribbon will be required for in situ fabrication of structural components via heated head advanced tow placement. To implement process control and ensure high quality ribbon, the ribbonizer heat transfer and pulling force were modeled from fundamental principles. Most of the new ribbons were fabricated from dry polyarylene ether and polymide powders.

  18. Laser Engineered Net Shaping (LENS(TM)): A Tool for Direct Fabrication of Metal Parts

    SciTech Connect

    Atwood, C.; Ensz, M.; Greene, D.; Griffith, M.; Harwell, L.; Reckaway, D.; Romero, T.; Schlienger, E.; Smugeresky, J.

    1998-11-05

    For many years, Sandia National Laboratories has been involved in the development and application of rapid prototyping and dmect fabrication technologies to build prototype parts and patterns for investment casting. Sandia is currently developing a process called Laser Engineered Net Shaping (LENS~) to fabricate filly dense metal parts dwectly from computer-aided design (CAD) solid models. The process is similar to traditional laser-initiated rapid prototyping technologies such as stereolithography and selective laser sintering in that layer additive techniques are used to fabricate physical parts directly from CAD data. By using the coordinated delivery of metal particles into a focused laser beam apart is generated. The laser beam creates a molten pool of metal on a substrate into which powder is injected. Concurrently, the substrate on which the deposition is occurring is moved under the beam/powder interaction zone to fabricate the desired cross-sectiwal geometry. Consecutive layers are additively deposited, thereby producing a three-dmensional part. This process exhibits enormous potential to revolutionize the way in which metal parts, such as complex prototypes, tooling, and small-lot production parts, are produced. The result is a comple~ filly dense, near-net-shape part. Parts have been fabricated from 316 stainless steel, nickel-based alloys, H13 tool steel, and titanium. This talk will provide a general overview of the LENS~ process, discuss potential applications, and display as-processed examples of parts.

  19. Diffractive optical elements fabricated for beam shaping of high-power diode lasers

    NASA Astrophysics Data System (ADS)

    Vogt, Helge; Biertümpfel, Ralf; Pawlowski, Edgar

    2008-02-01

    This paper discusses the use of diffractive optical elements (DOEs) and micro-optics fabricated by precise pressing in glass for beam shaping of high-power diode lasers. The DOEs are used to diffract the light into the point of interest and to improve the laser beam quality. We have realized circular, flat-top and multi-beam intensity profiles. The highest measured diffraction efficiency was higher than 95 %. The new established fabrication process has potential for mass production of DOEs. SCHOTT's precision glass molding process guarantees a very constant quality over the complete production chain.

  20. Fabrication and Characteristics of Free Standing Shaped Pupil Masks for TPF-Coronagraph

    NASA Technical Reports Server (NTRS)

    Balasubramanian, Kunjithapatham; Echternach, Pierre M.; Dickie, Matthew R.; Muller, Richard E.; White, Victor E.; Hoppe, Daniel J.; Shaklan, Stuart B.; Belikov, Ruslan; Kasdin, N. Jeremy; Vanderbei, Robert J.; Ceperley, Daniel; Neureuther, Andrew R.

    2006-01-01

    Direct imaging and characterization of exo-solar terrestrial planets require coronagraphic instruments capable of suppressing star light to 10-10. Pupil shaping masks have been proposed and designed1 at Princeton University to accomplish such a goal. Based on Princeton designs, free standing (without a substrate) silicon masks have been fabricated with lithographic and deep etching techniques. In this paper, we discuss the fabrication of such masks and present their physical and optical characteristics in relevance to their performance over the visible to near IR bandwidth.

  1. Bending properties of two- and three-dimensional-shaped nanoparticles fabricated via substrate conformal imprint lithography

    NASA Astrophysics Data System (ADS)

    Reuter, Sabrina; Smolarczyk, Marek A.; Istock, André; Ha, Uh-Myong; Schneider, Olga; Worapattrakul, Natalie; Nazemroaya, Safoura; Hoang, Hai; Gomer, Ludmilla; Pilger, Frank; Maniak, Markus; Hillmer, Hartmut

    2017-05-01

    Nanoimprinting enables the implementation of nanoparticle shapes with complex 2D shapes involving different materials. In addition to these objects, this article presents 3D-shaped nanoparticles fabricated by substrate conformal imprint technique. The imprint polymer AMONIL is used either in pure form or in combination with fluorescent dyes for the preparation of particles. The substrate conformal imprint lithography process, including etching and particle release, is conducted for both materials in a similar fashion. In this work, cuboidal particles with a high aspect ratio (1:120) are compared to particles with a T-shaped cross section with respect to their abilities to enhance or reduce their stiffness. Additionally, particles with a high aspect ratio are compared to particles with a lower aspect ratio (1:20). The local stiffness is found to depend strongly on the particle thickness and the geometry of their cross section. Thicker and 3D T-shaped particles present higher local stiffness than thinner and 2D cuboidal-shaped particles. The local bending angle was determined to be 77° for 2D-shaped particles and 83° for 3D-shaped particles, of the same total height of 176 nm. Very thin particles (<50 nm) of high aspect ratio prefer to curl finally forming loops.

  2. Laundering durable antibacterial cotton fabrics grafted with pomegranate-shaped polymer wrapped in silver nanoparticle aggregations

    PubMed Central

    Liu, Hanzhou; Lv, Ming; Deng, Bo; Li, Jingye; Yu, Ming; Huang, Qing; Fan, Chunhai

    2014-01-01

    To improve the laundering durability of the silver functionalized antibacterial cotton fabrics, a radiation-induced coincident reduction and graft polymerization is reported herein where a pomegranate-shaped silver nanoparticle aggregations up to 500 nm can be formed due to the coordination forces between amino group and silver and the wrapping procedure originated from the coincident growth of the silver nanoparticles and polymer graft chains. This pomegranate-shaped silver NPAs functionalized cotton fabric exhibits outstanding antibacterial activities and also excellent laundering durability, where it can inactivate higher than 90% of both E. coli and S. aureus even after 50 accelerated laundering cycles, which is equivalent to 250 commercial or domestic laundering cycles. PMID:25082297

  3. Fabrication of a smart air intake structure using shape memory alloy wire embedded composite

    NASA Astrophysics Data System (ADS)

    Jung, Beom-Seok; Kim, Min-Saeng; Kim, Ji-Soo; Kim, Yun-Mi; Lee, Woo-Yong; Ahn, Sung-Hoon

    2010-05-01

    Shape memory alloys (SMAs) have been actively studied in many fields utilizing their high energy density. Applying SMA wire-embedded composite to aerospace structures, such as air intake of jet engines and guided missiles, is attracting significant attention because it could generate a comparatively large actuating force. In this research, a scaled structure of SMA wire-embedded composite was fabricated for the air intake of aircraft. The structure was composed of several prestrained Nitinol (Ni-Ti) SMA wires embedded in ∩-shape glass fabric reinforced plastic (GFRP), and it was cured at room temperature for 72 h. The SMA wire-embedded GFRP could be actuated by applying electric current through the embedded SMA wires. The activation angle generated from the composite structure was large enough to make a smart air intake structure.

  4. Fabrication of cone-shaped boron doped diamond and gold nanoelectrodes for AFM-SECM

    NASA Astrophysics Data System (ADS)

    Avdic, A.; Lugstein, A.; Wu, M.; Gollas, B.; Pobelov, I.; Wandlowski, T.; Leonhardt, K.; Denuault, G.; Bertagnolli, E.

    2011-04-01

    We demonstrate a reliable microfabrication process for a combined atomic force microscopy (AFM) and scanning electrochemical microscopy (SECM) measurement tool. Integrated cone-shaped sensors with boron doped diamond (BDD) or gold (Au) electrodes were fabricated from commercially available AFM probes. The sensor formation process is based on mature semiconductor processing techniques, including focused ion beam (FIB) machining, and highly selective reactive ion etching (RIE). The fabrication approach preserves the geometry of the original AFM tips resulting in well reproducible nanoscaled sensors. The feasibility and functionality of the fully featured tips are demonstrated by cyclic voltammetry, showing good agreement between the measured and calculated currents of the cone-shaped AFM-SECM electrodes.

  5. Vision-based in-line fabric defect detection using yarn-specific shape features

    NASA Astrophysics Data System (ADS)

    Schneider, Dorian; Aach, Til

    2012-01-01

    We develop a methodology for automatic in-line flaw detection in industrial woven fabrics. Where state of the art detection algorithms apply texture analysis methods to operate on low-resolved ({200 ppi) image data, we describe here a process flow to segment single yarns in high-resolved ({1000 ppi) textile images. Four yarn shape features are extracted, allowing a precise detection and measurement of defects. The degree of precision reached allows a classification of detected defects according to their nature, providing an innovation in the field of automatic fabric flaw detection. The design has been carried out to meet real time requirements and face adverse conditions caused by loom vibrations and dirt. The entire process flow is discussed followed by an evaluation using a database with real-life industrial fabric images. This work pertains to the construction of an on-loom defect detection system to be used in manufacturing practice.

  6. Development of a method for fabricating metallic matrix composite shapes by a continuous mechanical process

    NASA Technical Reports Server (NTRS)

    Divecha, A. P.

    1974-01-01

    Attempts made to develop processes capable of producing metal composites in structural shapes and sizes suitable for space applications are described. The processes must be continuous and promise to lower fabrication costs. Special attention was given to the aluminum boride (Al/b) composite system. Results show that despite adequate temperature control, the consolidation characteristics did not improve as expected. Inadequate binder removal was identified as the cause responsible. An Al/c (aluminum-graphite) composite was also examined.

  7. A New Technique for Fabricating Three-Dimensional Micro- and Nanostructures of Various Shapes

    DTIC Science & Technology

    2001-06-01

    UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADP013151 TITLE: A New Technique for Fabricating Three-Dimensional Micro ...three-dimensional micro - and nanostructures of various shapes V. Ya. Prinz, D. Griitzmacher, A. Beyer, C. David, B. Ketterer and E. Deccard Laboratory...for Micro - and Nanotechnology, Paul Scherer Institute, CH-5232 Villigen PSI, Switzerland Abstract. We have shown that complex 3-dimensional micro - and

  8. Fine-tuned grayscale optofluidic maskless lithography for three-dimensional freeform shape microstructure fabrication.

    PubMed

    Song, Suk-Heung; Kim, Kibeom; Choi, Sung-Eun; Han, Sangkwon; Lee, Ho-Suk; Kwon, Sunghoon; Park, Wook

    2014-09-01

    This article presents free-floating three-dimensional (3D) microstructure fabrication in a microfluidic channel using direct fine-tuned grayscale image lithography. The image is designed as a freeform shape and is composed of gray shades as light-absorbing features. Gray shade levels are modulated through multiple reflections of light in a digital micromirror device (DMD) to produce different height formations. Whereas conventional photolithography has several limitations in producing grayscale colors on photomask features, our method focuses on a maskless, single-shot process for fabrication of freeform 3D micro-scale shapes. The fine-tuned gray image is designed using an 8-bit grayscale color; thus, each pixel is capable of displaying 256 gray shades. The pattern of the UV light reflecting on the DMD is transferred to a photocurable resin flowing through a microfluidic channel. Here, we demonstrate diverse free-floating 3D microstructure fabrication using fine-tuned grayscale image lithography. Additionally, we produce polymeric microstructures with locally embedded gray encoding patterns, such as grayscale-encoded microtags. This functional microstructure can be applied to a biophysical detection system combined with 3D microstructures. This method would be suitable for fabricating 3D microstructures that have a specific morphology to be used for particular biological or medical applications.

  9. Capacitive micromachined ultrasonic transducers with piston-shaped membranes: fabrication and experimental characterization.

    PubMed

    Huang, Yongli; Zhuang, Xuefeng; Haeggstrom, Edward O; Ergun, A Sanli; Cheng, Ching-Hsiang; Khuri-Yakub, Butrus T

    2009-01-01

    Capacitive micromachined ultrasonic transducers (CMUTs) featuring piston-shaped membranes (piston CMUTs) were developed to improve device performance in terms of transmission efficiency, reception sensitivity, and fractional bandwidth (FBW). A piston CMUT has a relatively flat active moving surface whose membrane motion is closer to ideal piston-type motion compared with a CMUT with uniformly thick membranes (classical CMUT). Piston CMUTs with a more uniform surface displacement profile can achieve high output pressure with a relatively small electrode separation. The improved device capacitance and gap uniformity also enhance detection sensitivity. By adding a center mass to the membrane, a large ratio of second-order resonant frequency to first-order resonant frequency was achieved. This improved the FBW. Piston CMUTs featuring membranes of different geometric shapes were designed and fabricated using wafer bonding. Fabricating piston CMUTs is a more complex process than fabricating CMUTs with uniformly thick membranes. However, no yield loss was observed. These devices achieved ~100% improvement in transduction performance (transmission and reception) over classical CMUTs. For CMUTs with square and rectangular membranes, the FBW increased from ~110% to ~150% and from ~140% to ~175%, respectively, compared with classical CMUTs. The new devices produced a maximum output pressure exceeding 1 MPa at the transducer surface. Performance optimization using geometric membrane shape configurations was the same in both piston CMUTs and classical CMUTs.

  10. Microfluidic Fabrication of Polymeric and Biohybrid Fibers with Predesigned Size and Shape

    PubMed Central

    Boyd, Darryl A.; Adams, Andre A.; Daniele, Michael A.; Ligler, Frances S.

    2014-01-01

    A “sheath” fluid passing through a microfluidic channel at low Reynolds number can be directed around another “core” stream and used to dictate the shape as well as the diameter of a core stream. Grooves in the top and bottom of a microfluidic channel were designed to direct the sheath fluid and shape the core fluid. By matching the viscosity and hydrophilicity of the sheath and core fluids, the interfacial effects are minimized and complex fluid shapes can be formed. Controlling the relative flow rates of the sheath and core fluids determines the cross-sectional area of the core fluid. Fibers have been produced with sizes ranging from 300 nm to ~1 mm, and fiber cross-sections can be round, flat, square, or complex as in the case with double anchor fibers. Polymerization of the core fluid downstream from the shaping region solidifies the fibers. Photoinitiated click chemistries are well suited for rapid polymerization of the core fluid by irradiation with ultraviolet light. Fibers with a wide variety of shapes have been produced from a list of polymers including liquid crystals, poly(methylmethacrylate), thiol-ene and thiol-yne resins, polyethylene glycol, and hydrogel derivatives. Minimal shear during the shaping process and mild polymerization conditions also makes the fabrication process well suited for encapsulation of cells and other biological components. PMID:24430733

  11. Fabrication and characterization of Pac-man shaped magnetic tunneling junctions

    NASA Astrophysics Data System (ADS)

    Han, Hongmei

    As the basic information cell in a magnetic random access memory (MRAM), magnetic tunneling junction (MTJ) and the addressing of its integration issues with the existing silicon technology are critical to improve its performance and competitiveness compared to other emerging RAM technologies. This dissertation uses micromagnetic modeling and microelectronic fabrication method to study the magnetic cell's shape effect on MTJ's magnetic and transport properties. In addition, integration of MTJ on the CMOS line processed metal pads is demonstrated with university facilities. From micromagnetic simulation, a proposed comma-shaped elongated Pac-man (EPM) shows the best-combined cell selectivity and switching characteristics compared to the existing ellipse and Saturn shapes. Its tilted effective easy axis broke the symmetry of the 'astroid', where enlarged operating window and increased half-selection resistance in the 1st and 3 rd quadrants are observed. A back-to-back paired configuration of two 180-EPMs (or half ellipse) and a multi-state MRAM paired cell design are proposed to effectively increase the MRAM density. The results from e-beam patterned magnetic elements match with the micromagnetic simulations. Various sized MTJs with rectangular, parallelogram, trapezoid and Pac-man shapes are fabricated and studied. Shape mainly affects MTJ's switching characteristics through the variation of its demagnetization field distribution. The integrated rectangular shaped MTJ tends to form vortex which reduces its MR signal up to 60%. MTJ with trapezoid shape shows better properties compared to the parallelogram shaped MTJ due to its confined demagnetic field configuration. Array of 8x8 180-EPM shaped MTJs have narrow switching field distribution. As MTJ's size reduces, its switching field increases noticeably. The quality of MTJ's barrier layer significantly affects its magnetoresistance (MR). Coupling between the free and fixed layers in a MTJ is detrimental to its MR

  12. Fabrication

    NASA Astrophysics Data System (ADS)

    Angel, Roger; Helms, Richard; Bilbro, Jim; Brown, Norman; Eng, Sverre; Hinman, Steve; Hull-Allen, Greg; Jacobs, Stephen; Keim, Robert; Ulmer, Melville

    1992-08-01

    What aspects of optical fabrication technology need to be developed so as to facilitate existing planned missions, or enable new ones? Throughout the submillimeter to UV wavelengths, the common goal is to push technology to the limits to make the largest possible apertures that are diffraction limited. At any one wavelength, the accuracy of the surface must be better than lambda/30 (rms error). The wavelength range is huge, covering four orders of magnitude from 1 mm to 100 nm. At the longer wavelengths, diffraction limited surfaces can be shaped with relatively crude techniques. The challenge in their fabrication is to make as large as possible a reflector, given the weight and volume constraints of the launch vehicle. The limited cargo diameter of the shuttle has led in the past to emphasis on deployable or erectable concepts such as the Large Deployable Reflector (LDR), which was studied by NASA for a submillimeter astrophysics mission. Replication techniques that can be used to produce light, low-cost reflecting panels are of great interest for this class of mission. At shorter wavelengths, in the optical and ultraviolet, optical fabrication will tax to the limit the most refined polishing methods. Methods of mechanical and thermal stabilization of the substrate will be severely stressed. In the thermal infrared, the need for large aperture is tempered by the even stronger need to control the telescope's thermal emission by cooled or cryogenic operation. Thus, the SIRTF mirror at 1 meter is not large and does not require unusually high accuracy, but the fabrication process must produce a mirror that is the right shape at a temperature of 4 K. Future large cooled mirrors will present more severe problems, especially if they must also be accurate enough to work at optical wavelengths. At the very shortest wavelengths accessible to reflecting optics, in the x-ray domain, the very low count fluxes of high energy photons place a premium on the collecting area. It is

  13. Fabrication

    NASA Technical Reports Server (NTRS)

    Angel, Roger; Helms, Richard; Bilbro, Jim; Brown, Norman; Eng, Sverre; Hinman, Steve; Hull-Allen, Greg; Jacobs, Stephen; Keim, Robert; Ulmer, Melville

    1992-01-01

    What aspects of optical fabrication technology need to be developed so as to facilitate existing planned missions, or enable new ones? Throughout the submillimeter to UV wavelengths, the common goal is to push technology to the limits to make the largest possible apertures that are diffraction limited. At any one wavelength, the accuracy of the surface must be better than lambda/30 (rms error). The wavelength range is huge, covering four orders of magnitude from 1 mm to 100 nm. At the longer wavelengths, diffraction limited surfaces can be shaped with relatively crude techniques. The challenge in their fabrication is to make as large as possible a reflector, given the weight and volume constraints of the launch vehicle. The limited cargo diameter of the shuttle has led in the past to emphasis on deployable or erectable concepts such as the Large Deployable Reflector (LDR), which was studied by NASA for a submillimeter astrophysics mission. Replication techniques that can be used to produce light, low-cost reflecting panels are of great interest for this class of mission. At shorter wavelengths, in the optical and ultraviolet, optical fabrication will tax to the limit the most refined polishing methods. Methods of mechanical and thermal stabilization of the substrate will be severely stressed. In the thermal infrared, the need for large aperture is tempered by the even stronger need to control the telescope's thermal emission by cooled or cryogenic operation. Thus, the SIRTF mirror at 1 meter is not large and does not require unusually high accuracy, but the fabrication process must produce a mirror that is the right shape at a temperature of 4 K. Future large cooled mirrors will present more severe problems, especially if they must also be accurate enough to work at optical wavelengths. At the very shortest wavelengths accessible to reflecting optics, in the x-ray domain, the very low count fluxes of high energy photons place a premium on the collecting area. It is

  14. Simulation and Fabrication of Wagon-Wheel-Shaped Piezoelectric Transducer for Raindrop Energy Harvesting Application

    NASA Astrophysics Data System (ADS)

    Wong, Chin Hong; Dahari, Zuraini; Jumali, Mohammad Hafizuddin; Mohamed, Khairudin; Mohamed, Julie Juliewatty

    2017-01-01

    Harvesting vibrational energy from impacting raindrops using piezoelectric material has been proven to be a promising approach for future outdoor applications, providing a good alternative resource that can be applied in outdoor rainy environments. We present herein an optimum novel polyvinylidene fluoride (PVDF) piezoelectric transducer specifically developed to harvest raindrop energy. The finite-element method was applied for simulation and optimization of the piezoelectric raindrop energy harvester (PREH) using COMSOL Multiphysics software, investigating the electrical potential, surface charge density, and total displacement for different transducer dimensions. According to the simulation results, the structure that generated the highest electrical potential and surface charge density was a wagon-wheel-shaped structure consisting of six spokes with wheel diameter of 30 mm, spoke width of 2 mm, center pad diameter of 6 mm, and thickness of 25 μm. This optimum wagon-wheel-shaped device was then fabricated by spin coating of PVDF, sputtering of aluminum, a poling process, and computer numerical control machining of a polytetrafluoroethylene stand. The fabricated PREH was characterized by x-ray diffraction analysis and Fourier-transform infrared spectroscopy. Finally, the fabricated PREH was tested under actual rain conditions with an alternating current to direct current converter connected in parallel, revealing that a single cell could generate average peak voltage of 22.5 mV and produce electrical energy of 3.4 nJ from ten impacts in 20 s.

  15. Microstereolithography-Based Fabrication of Anatomically Shaped Beta-Tricalcium Phosphate Scaffolds for Bone Tissue Engineering

    PubMed Central

    Du, Dajiang; Asaoka, Teruo; Shinohara, Makoto; Kageyama, Tomonori; Ushida, Takashi; Furukawa, Katsuko Sakai

    2015-01-01

    Porous ceramic scaffolds with shapes matching the bone defects may result in more efficient grafting and healing than the ones with simple geometries. Using computer-assisted microstereolithography (MSTL), we have developed a novel gelcasting indirect MSTL technology and successfully fabricated two scaffolds according to CT images of rabbit femur. Negative resin molds with outer 3D dimensions conforming to the femur and an internal structure consisting of stacked meshes with uniform interconnecting struts, 0.5 mm in diameter, were fabricated by MSTL. The second mold type was designed for cortical bone formation. A ceramic slurry of beta-tricalcium phosphate (β-TCP) with room temperature vulcanization (RTV) silicone as binder was cast into the molds. After the RTV silicone was completely cured, the composite was sintered at 1500°C for 5 h. Both gross anatomical shape and the interpenetrating internal network were preserved after sintering. Even cortical structure could be introduced into the customized scaffolds, which resulted in enhanced strength. Biocompatibility was confirmed by vital staining of rabbit bone marrow mesenchymal stromal cells cultured on the customized scaffolds for 5 days. This fabrication method could be useful for constructing bone substitutes specifically designed according to local anatomical defects. PMID:26504839

  16. Simulation and Fabrication of Wagon-Wheel-Shaped Piezoelectric Transducer for Raindrop Energy Harvesting Application

    NASA Astrophysics Data System (ADS)

    Wong, Chin Hong; Dahari, Zuraini; Jumali, Mohammad Hafizuddin; Mohamed, Khairudin; Mohamed, Julie Juliewatty

    2017-03-01

    Harvesting vibrational energy from impacting raindrops using piezoelectric material has been proven to be a promising approach for future outdoor applications, providing a good alternative resource that can be applied in outdoor rainy environments. We present herein an optimum novel polyvinylidene fluoride (PVDF) piezoelectric transducer specifically developed to harvest raindrop energy. The finite-element method was applied for simulation and optimization of the piezoelectric raindrop energy harvester (PREH) using COMSOL Multiphysics software, investigating the electrical potential, surface charge density, and total displacement for different transducer dimensions. According to the simulation results, the structure that generated the highest electrical potential and surface charge density was a wagon-wheel-shaped structure consisting of six spokes with wheel diameter of 30 mm, spoke width of 2 mm, center pad diameter of 6 mm, and thickness of 25 μm. This optimum wagon-wheel-shaped device was then fabricated by spin coating of PVDF, sputtering of aluminum, a poling process, and computer numerical control machining of a polytetrafluoroethylene stand. The fabricated PREH was characterized by x-ray diffraction analysis and Fourier-transform infrared spectroscopy. Finally, the fabricated PREH was tested under actual rain conditions with an alternating current to direct current converter connected in parallel, revealing that a single cell could generate average peak voltage of 22.5 mV and produce electrical energy of 3.4 nJ from ten impacts in 20 s.

  17. Net shape fabrication of calcium phosphate scaffolds with multiple material domains.

    PubMed

    Xie, Yangmin; Rustom, Laurence E; McDermott, Anna M; Boerckel, Joel D; Johnson, Amy J Wagoner; Alleyne, Andrew G; Hoelzle, David J

    2016-01-08

    Calcium phosphate (CaP) materials have been proven to be efficacious as bone scaffold materials, but are difficult to fabricate into complex architectures because of the high processing temperatures required. In contrast, polymeric materials are easily formed into scaffolds with near-net-shape forms of patient-specific defects and with domains of different materials; however, they have reduced load-bearing capacity compared to CaPs. To preserve the merits of CaP scaffolds and enable advanced scaffold manufacturing, this manuscript describes an additive manufacturing process that is coupled with a mold support for overhanging features; we demonstrate that this process enables the fabrication of CaP scaffolds that have both complex, near-net-shape contours and distinct domains with different microstructures. First, we use a set of canonical structures to study the manufacture of complex contours and distinct regions of different material domains within a mold. We then apply these capabilities to the fabrication of a scaffold that is designed for a 5 cm orbital socket defect. This scaffold has complex external contours, interconnected porosity on the order of 300 μm throughout, and two distinct domains of different material microstructures.

  18. Novel processes for near net-shaped fabrication of monolithic and reinforced oxide ceramics

    NASA Astrophysics Data System (ADS)

    Kumar, Pragati

    Mg reinforced Alsb2Osb3 composites were fabricated by pressureless infiltration of molten Mg into porous Alsb2Osb3 preforms. Such pressureless infiltration is thought to be driven by a displacement reaction that was observed to occur at interfaces between liquid Mg and solid Alsb2Osb3. The feasibility of fabricating near net-shaped, monolithic, MgAlsb2Osb4 spinel bodies by the oxidation of the solid Mg-Alsb2Osb3-bearing composites was demonstrated. By controlling the preform porosity and the infiltration conditions, Mg-Alsb2Osb3-bearing composite bodies could be produced with the proper overall stoichiometry for spinel. The Mg/Alsb2Osb3 composites could be machined into complex shapes. Oxidation of the Mg in the shaped composite was conducted in pure, flowing oxygen at 430{-}700sp°C. Post-oxidation annealing at 1200sp°C then allowed for complete conversion of MgO-Alsb2Osb3 bearing body into MgAlsb2Osb4 spinel. A final sintering treatment in flowing Ar at 1700sp°C yielded spinel specimens with densities ≥92%. The sintered spinel bodies retained the Mg-Alsb2Osb3-bearing precursor shape and dimensions (to within 0.63%). The fabrication of spinel-matrix composites is also discussed. In addition, a novel approach is presented for the fabrication of dense, shaped ceramic/metal composites by a novel class of displacement reactions. This approach differs from other oxidation-based processes for fabricating near net-shaped oxide/metal composites (e.g. DIMOX, Csp4) in that a reaction-induced volume expansion is used to compensate for the porosity within a preform, so as to yield a dense composite with a high ceramic content. In the present case, a displacement reaction between liquid Mg and solid Alsb2Osb3 was used to produce composites of MgO and Mg-bearing metal. Porous, shaped Alsb2Osb3 preforms were placed in contact with a Mg(l) bath at 1000sp°C. The liquid Mg completely infiltrated and consumed the Alsb2Osb3 preform by the following net reaction:$3Mg(l) + Alsb2

  19. Shape, Loading, and Motion in the Bioengineering Design, Fabrication, and Testing of Personalized Synovial Joints

    PubMed Central

    Williams, Gregory M.; Chan, Elaine F.; Temple-Wong, Michele M.; Bae, Won C.; Masuda, Koichi; Bugbee, William D.; Sah, Robert L.

    2009-01-01

    With continued development and improvement of tissue engineering therapies for small articular lesions, increased attention is being focused on the challenge of engineering partial or whole synovial joints. Joint-scale constructs could have applications in the treatment of large areas of articular damage or in biological arthroplasty of severely degenerate joints. This review considers the roles of shape, loading and motion in synovial joint mechanobiology and their incorporation into the design, fabrication, and testing of engineered partial or whole joints. Incidence of degeneration, degree of impairment, and efficacy of current treatments are critical factors in choosing a target for joint bioengineering. The form and function of native joints may guide the design of engineered joint-scale constructs with respect to size, shape, and maturity. Fabrication challenges for joint-scale engineering include controlling chemo-mechano-biological microenvironments to promote the development and growth of multiple tissues with integrated interfaces or lubricated surfaces into anatomical shapes, and joint-scale bioreactors which nurture and stimulate the tissue with loading and motion. Finally, evaluation of load-bearing and tribological properties can range from tissue to joint scale and can focus on biological structure at present or after adaptation. PMID:19815214

  20. Novel biodegradable star-shaped polylactide scaffolds for bone regeneration fabricated by two-photon polymerization.

    PubMed

    Timashev, Peter; Kuznetsova, Daria; Koroleva, Anastasia; Prodanets, Natalia; Deiwick, Andrea; Piskun, Yuri; Bardakova, Ksenia; Dzhoyashvili, Nina; Kostjuk, Sergei; Zagaynova, Elena; Rochev, Yuri; Chichkov, Boris; Bagratashvili, Viktor

    2016-05-01

    To assess the properties of 3D biodegradable scaffolds fabricated from novel star-shaped poly(D,L-lactide) (SSL) materials for bone tissue regeneration. The SSL polymer was synthesized using an optimized synthetic procedure and applied for scaffold fabrication by the two-photon polymerization technique. The osteogenic differentiation was controlled using human adipose-derived stem cells cultured for 28 days. The SSL scaffolds with or without murine MSCs were implanted into the cranial bone of C57/Bl6 mice. The SSL scaffolds supported differentiation of human adipose-derived stem cells toward the osteogenic lineage in vitro. The SSL scaffolds with murine MSCs enhanced the mineralized tissue formation. The SSL scaffolds provide a beneficial microenvironment for the osteogenic MSCs' differentiation in vitro and support de novo bone formation in vivo.

  1. Fabrication of different pore shapes by multi-step etching technique in ion-irradiated PET membranes

    NASA Astrophysics Data System (ADS)

    Mo, D.; Liu, J. D.; Duan, J. L.; Yao, H. J.; Latif, H.; Cao, D. L.; Chen, Y. H.; Zhang, S. X.; Zhai, P. F.; Liu, J.

    2014-08-01

    A method for the fabrication of different pore shapes in polyethylene terephthalate (PET)-based track etched membranes (TEMs) is reported. A multi-step etching technique involving etchant variation and track annealing was applied to fabricate different pore shapes in PET membranes. PET foils of 12-μm thickness were irradiated with Bi ions (kinetic energy 9.5 MeV/u, fluence 106 ions/cm2) at the Heavy Ion Research Facility (HIRFL, Lanzhou). The cross-sections of fundamental pore shapes (cylinder, cone, and double cone) were analyzed. Funnel-shaped and pencil-shaped pores were obtained using a two-step etching process. Track annealing was carried out in air at 180 °C for 120 min. After track annealing, the selectivity of the etching process decreased, which resulted in isotropic etching in subsequent etching steps. Rounded cylinder and rounded cone shapes were obtained by introducing a track-annealing step in the etching process. Cup and spherical funnel-shaped pores were fabricated using a three- and four-step etching process, respectively. The described multi-step etching technique provides a controllable method to fabricate new pore shapes in TEMs. Introduction of a variety of pore shapes may improve the separation properties of TEMs and enrich the series of TEM products.

  2. Free form fabrication using the laser engineered net shaping (LENS{trademark}) process

    SciTech Connect

    Keicher, D.M.; Romero, J.A.; Atwood, C.L.; Griffith, M.L.; Jeantette, F.P.; Harwell, L.D.; Greene, D.L.; Smugeresky, J.E.

    1996-12-31

    Sandia National Laboratories is developing a technology called Laser Engineered Net Shaping{trademark} (LENS{trademark}). This process allows complex 3-dimensional solid metallic objects to be directly fabricated for a CAD solid model. Experiments performed demonstrate that complex alloys such as Inconel{trademark} 625 and ANSI stainless steel alloy 316 can be used in the LENS{trademark} process to produce solid metallic-shapes. In fact, the fabricated structures exhibit grain growth across the deposition layer boundaries. Mechanical testing data of deposited 316 stainless steel material indicates that the deposited material strength and elongation are greater than that reported for annealed 316 stainless steel. Electron microprobe analysis of the deposited Inconel{trademark} 625 material shows no compositional degradation of the 625 alloy and that 100% dense structures can be obtained using this technique. High speed imaging used to acquire process data during experimentation shows that the powder particle size range can significantly affect the stability, and subsequently, the performance of the powder deposition process. Finally, dimensional studies suggest that dimensional accuracy to {+-} 0.002 inches (in the horizontal direction) can be maintained.

  3. Fabrication and In Vitro Deployment of a Laser-Activated Shape Memory Polymer Vascular Stent

    SciTech Connect

    Baer, G M; Small IV, W; Wilson, T S; Benett, W J; Matthews, D L; Hartman, J; Maitland, D J

    2007-04-25

    Vascular stents are small tubular scaffolds used in the treatment of arterial stenosis (narrowing of the vessel). Most vascular stents are metallic and are deployed either by balloon expansion or by self-expansion. A shape memory polymer (SMP) stent may enhance flexibility, compliance, and drug elution compared to its current metallic counterparts. The purpose of this study was to describe the fabrication of a laser-activated SMP stent and demonstrate photothermal expansion of the stent in an in vitro artery model. A novel SMP stent was fabricated from thermoplastic polyurethane. A solid SMP tube formed by dip coating a stainless steel pin was laser-etched to create the mesh pattern of the finished stent. The stent was crimped over a fiber-optic cylindrical light diffuser coupled to an infrared diode laser. Photothermal actuation of the stent was performed in a water-filled mock artery. At a physiological flow rate, the stent did not fully expand at the maximum laser power (8.6 W) due to convective cooling. However, under zero flow, simulating the technique of endovascular flow occlusion, complete laser actuation was achieved in the mock artery at a laser power of {approx}8 W. We have shown the design and fabrication of an SMP stent and a means of light delivery for photothermal actuation. Though further studies are required to optimize the device and assess thermal tissue damage, photothermal actuation of the SMP stent was demonstrated.

  4. Fabrication and characterization of graphitic carbon nanostructures with controllable size, shape, and position.

    PubMed

    Du, Rongbing; Ssenyange, Solomon; Aktary, Mirwais; McDermott, Mark T

    2009-05-01

    The incorporation of carbon materials in micro- and nanoscale devices is being widely investigated due to the promise of enhanced functionality. Challenges in the positioning and addressability of carbon nanotubes provide the motivation for the development of new processes to produce nanoscale carbon materials. Here, the fabrication of conducting, nanometer-sized carbon structures using a combination of electron beam lithography (EBL) and carbonisation is reported. EBL is used to directly write predefined nanometer-sized patterns in a thin layer of negative resist in controllable locations. Careful heat treatment results in carbon nanostructures with the size, shape, and location originally defined by EBL. The pyrolysis process results in significant shrinkage of the structures in the vertical direction and minimal loss in the horizontal direction. Characterization of the carbonized material indicates a structure consisting of both amorphous and graphitized carbon with low levels of oxygen. The resistivity of the material is similar to other disordered carbon materials and the resistivity is maintained from the bulk to the nanoscale. This is demonstrated by fabricating a nanoscale structure with predictable resistance. The ability to fabricate these conductive structures with known dimensions and in predefined locations can be exploited for a number of applications. Their use as nanoband electrodes is also demonstrated.

  5. Facile moldless fabrication of disk-shaped and reed blood cell-like microparticles using photopolymerization of tripropylene glycol diacrylate

    NASA Astrophysics Data System (ADS)

    Choi, Jongchul; Won, June; Song, Simon

    2014-12-01

    A facile method for the moldless fabrication of 2- or 3-dimensional microparticles is proposed by using a photopolymerization technique. Using only a monomer solution of tripropylene glycol diacrylate, a film mask and standard UV lithography equipment, we were able to fabricate microparticles of various shapes, such as disks, dimpled disks similar in shape to red blood cells, and slender gourd shapes, unlike previous moldless fabrication techniques requiring expensive and/or sophisticated equipment. The simple method could produce more than one million particles in a single batch, indicating that it can be applied to the mass production of polymer microparticles. Analyses of scanning electron micrographs and optical micrographs of the microparticles indicated that their size distribution was highly monodisperse. Detailed fabrication processes and statistics on the microparticle sizes are given in this paper.

  6. A fabrication method of unique Nafion® shapes by painting for ionic polymer-metal composites

    NASA Astrophysics Data System (ADS)

    Trabia, Sarah; Hwang, Taeseon; Kim, Kwang J.

    2016-08-01

    Ionic polymer-metal composites (IPMC) are useful actuators because of their ability to be fabricated in different shapes and move in various ways. However, producing unique or intricate shapes can be difficult based upon the current fabrication techniques. Presented here is a fabrication method of producing the Nafion® membrane or thin film through a painting method. Using an airbrush, a Nafion water dispersion is sprayed onto an acrylonitrile butadiene styrene surface with a stencil of the desired shape. To verify that this method of fabrication produces a Nafion membrane similar to that which is commercially available, a sample that was made using the painting method and Nafion 117 purchased from DuPont™ were tested for various characteristics and compared. The results show promising similarities. The painted Nafion sample was chemically plated with platinum and compared with a traditional IPMC for its displacement and blocking force capabilities. The painted IPMC sample showed comparable results.

  7. Fabrication method of 3D feed horn shape MEMS antenna array using MRPBI system and application for microbolometer

    NASA Astrophysics Data System (ADS)

    Park, Jong-Yeon; Kim, Kuntae; Moon, Sung; Park, Jong-Oh; Oh, Myung-Hwan; Pak, James Jungho

    2001-11-01

    A 3D Feed horn shape MEMS antenna has some attractive features for array application, which can be used to improve microbolometer performance. Since MEMS technology have been faced many difficulties to fabrication of 3D feed horn shape MEMS antenna array itself. The purpose of this paper is to propose a new fabrication method to realize a 3D feed horn shape MEMS antenna array using a MRPBI(Mirror Reflected Parallel Beam Illuminator) system with an ultra-slow-rotated and inclined x-y-z stage. A high-aspect-ratio 300 micrometers sidewalls had been fabricated using SU-8 negative photo resist. It can be demonstrated to feasibility of realize 3D feed horn shape MEMS antenna array fabrication. In order to study the effect of this novel technique, the 3D feed horn shape MEMS antenna array had been simulated with HFSS(High Frequency Structure Simulator) tools and then compared with traditional 3D theoretical antenna models. As a result, it seems possible to use a 3D feed horn shape MEMS antenna at the tera hertz band to improve microbolometer performance and optical MEMS device fabrication.

  8. Direct-write fabrication of 4D active shape-changing behavior based on a shape memory polymer and its nanocomposite (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Wei, Hongqiu; Zhang, Qiwei; Yao, Yongtao; Liu, Liwu; Liu, Yanju; Leng, Jinsong

    2017-04-01

    Shape memory polymers (SMPs), a typical class of smart materials, have been witnessed significant advances in the past decades. Based on the unique performance to recover the initial shape after going through a shape deformation, the applications of SMPs have aroused growing interests. However, most of the researches are hindered by traditional processing technologies which limit the design space of SMPs-based structures. Three-dimension (3D) printing as an emerging technology endows design freedom to manufacture materials with complex structures. In present article, we show that by employing direct-write printing method; one can realize the printing of SMPs to achieve 4D active shape-changing structures. We first fabricated a kind of 3D printable polylactide (PLA)-based SMPs and characterized the overall properties of such materials. Results demonstrated the prepared PLA-based SMPs presenting excellent shape memory effect. In what follows, the rheological properties of such PLA-based SMP ink during printing process were discussed in detail. Finally, we designed and printed several 3D configurations for investigation. By combining 3D printing with shape memory behavior, these printed structures achieve 4D active shape-changing performance under heat stimuli. This research presents a high flexible method to realize the fabrication of SMP-based 4D active shape-changing structures, which opens the way for further developments and improvements of high-tech fields like 4D printing, soft robotics, micro-systems and biomedical devices.

  9. Design and fabrication of uniquely shaped thiol-ene microfibers using a two-stage hydrodynamic focusing design.

    PubMed

    Boyd, Darryl A; Shields, Adam R; Howell, Peter B; Ligler, Frances S

    2013-08-07

    Microfluidic systems have advantages that are just starting to be realized for materials fabrication. In addition to the more common use for fabrication of particles, hydrodynamic focusing has been used to fabricate continuous polymer fibers. We have previously described such a microfluidics system which has the ability to generate fibers with controlled cross-sectional shapes locked in place by in situ photopolymerization. The previous fiber fabrication studies produced relatively simple round or ribbon shapes, demonstrated the use of a variety of polymers, and described the interaction between sheath-core flow-rate ratios used to control the fiber diameter and the impact on possible shapes. These papers documented the fact that no matter what the intended shape, higher flow-rate ratios produced rounder fibers, even in the absence of interfacial tension between the core and sheath fluids. This work describes how to fabricate the next generation of fibers predesigned to have a much more complex geometry, as exemplified by the "double anchor" shape. Critical to production of the pre-specified fibers with complex features was independent control over both the shape and the size of the fabricated microfibers using a two-stage hydrodynamic focusing system. Design and optimization of the channels was performed using finite element simulations and confocal imaging to characterize each of the two stages theoretically and experimentally. The resulting device design was then used to generate thiol-ene fibers with a unique double anchor shape. Finally, proof-of-principle functional experiments demonstrated the ability of the fibers to transport fluids and to interlock laterally.

  10. Efficient convolutional sparse coding

    DOEpatents

    Wohlberg, Brendt

    2017-06-20

    Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

  11. Fabrication of shape controlled Fe{sub 3}O{sub 4} nanostructure

    SciTech Connect

    Zheng, Y.Y.; Wang, X.B.; Shang, L.; Li, C.R.; Cui, C.; Dong, W.J.; Tang, W.H.; Chen, B.Y.

    2010-04-15

    Shape-controlled Fe{sub 3}O{sub 4} nanostructure has been successfully prepared using polyethylene glycol as template in a water system at room temperature. Different morphologies of Fe{sub 3}O{sub 4} nanostructures, including spherical, cubic, rod-like, and dendritic nanostructure, were obtained by carefully controlling the concentration of the Fe{sup 3+}, Fe{sup 2+}, and the molecular weight of the polyethylene glycol. Transmission Electron Microscope images, X-ray powder diffraction patterns and magnetic properties were used to characterize the final product. This easy procedure for Fe{sub 3}O{sub 4} nanostructure fabrication offers the possibility of a generalized approach to the production of single and complex nanocrystalline oxide with tunable morphology.

  12. Lipid Nanotube Tailored Fabrication of Uniquely Shaped Polydopamine Nanofibers as Photothermal Converters.

    PubMed

    Ding, Wuxiao; Chechetka, Svetlana A; Masuda, Mitsutoshi; Shimizu, Toshimi; Aoyagi, Masaru; Minamikawa, Hiroyuki; Miyako, Eijiro

    2016-03-18

    Helically coiled and linear polydopamine (PDA) nanofibers were selectively fabricated with two different types of lipid nanotubes (LNTs) that acted as templates. The obtained coiled PDA-LNT hybrid showed morphological advantages such as higher light absorbance and photothermal conversion effect compared to a linear counterpart. Laser irradiation of the coiled PDA-LNT hybrid induced a morphological change and subsequent release of the encapsulated guest molecule. In cellular experiments, the coiled PDA-LNT efficiently eliminated HeLa cells because of its strong affinity with the tumor cells. This work illustrates the first approach to construct characteristic morphologies of PDA nanofibers using LNTs as simple templates, and the coiled PDA-LNT hybrid exhibits attractive photothermal features derived from its unique coiled shape. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. WFIRST-AFTA coronagraph shaped pupil masks: design, fabrication, and characterization

    NASA Astrophysics Data System (ADS)

    Balasubramanian, Kunjithapatham; White, Victor; Yee, Karl; Echternach, Pierre; Muller, Richard; Dickie, Matthew; Cady, Eric; Prada, Camilo Mejia; Ryan, Daniel; Poberezhskiy, Ilya; Kern, Brian; Zhou, Hanying; Krist, John; Nemati, Bijan; Eldorado Riggs, A. J.; Zimmerman, Neil T.; Kasdin, N. Jeremy

    2016-01-01

    NASA WFIRST-AFTA mission study includes a coronagraph instrument to find and characterize exoplanets. Various types of masks could be employed to suppress the host starlight to about 10-9 level contrast over a broad spectrum to enable the coronagraph mission objectives. Such masks for high-contrast internal coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultralow reflectivity regions, uniformity, wave front quality, and achromaticity. We present the approaches employed at JPL to produce pupil plane and image plane coronagraph masks by combining electron beam, deep reactive ion etching, and black silicon technologies with illustrative examples of each, highlighting milestone accomplishments from the High Contrast Imaging Testbed at JPL and from the High Contrast Imaging Lab at Princeton University.

  14. Fabrication and Characterization of Cylindrical Light Diffusers Comprised of Shape Memory Polymer

    SciTech Connect

    Small IV, W; Buckley, P R; Wilson, T S; Loge, J M; Maitland, K D; Maitland, D J

    2007-01-29

    We have developed a technique for constructing light diffusing devices comprised of a flexible shape memory polymer (SMP) cylindrical diffuser attached to the tip of an optical fiber. Devices were fabricated by casting an SMP rod over the cleaved tip of an optical fiber and media blasting the SMP rod to create a light diffusing surface. The axial and polar emission profiles and circumferential (azimuthal) uniformity were characterized for various blasting pressures, nozzle-to-sample distances, and nozzle translation speeds. The diffusers were generally strongly forward-directed and consistently withstood over 8 W of incident infrared laser light without suffering damage when immersed in water. These devices are suitable for various endoluminal and interstitial biomedical applications.

  15. Shape-Controlled Fabrication of the Polymer-Based Micromotor Based on the Polydimethylsiloxane Template.

    PubMed

    Su, Miaoda; Liu, Mei; Liu, Limei; Sun, Yunyu; Li, Mingtong; Wang, Dalei; Zhang, Hui; Dong, Bin

    2015-11-03

    We report the utilization of the polydimethylsiloxane template to construct polymer-based autonomous micromotors with various structures. Solid or hollow micromotors, which consist of polycaprolactone and platinum nanoparticles, can be obtained with controllable sizes and shapes. The resulting micromotor can not only be self-propelled in solution based on the bubble propulsion mechanism in the presence of the hydrogen peroxide fuel, but also exhibit structure-dependent motion behavior. In addition, the micromotors can exhibit various functions, ranging from fluorescence, magnetic control to cargo transportation. Since the current method can be extended to a variety of organic and inorganic materials, we thus believe it may have great potential in the fabrication of different functional micromotors for diverse applications.

  16. Exoplanet Coronagraph Shaped Pupil Masks and Laboratory Scale Star Shade Masks: Design, Fabrication and Characterization

    NASA Technical Reports Server (NTRS)

    Balasubramanian, Kunjithapatha; White, Victor; Yee, Karl; Echternach, Pierre; Muller, Richard; Dickie, Matthew; Cady, Eric; Mejia Prada, Camilo; Ryan, Daniel; Poberezhskiy, Ilya; hide

    2015-01-01

    Star light suppression technologies to find and characterize faint exoplanets include internal coronagraph instruments as well as external star shade occulters. Currently, the NASA WFIRST-AFTA mission study includes an internal coronagraph instrument to find and characterize exoplanets. Various types of masks could be employed to suppress the host star light to about 10 -9 level contrast over a broad spectrum to enable the coronagraph mission objectives. Such masks for high contrast internal coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultra-low reflectivity regions, uniformity, wave front quality, achromaticity, etc. We present the approaches employed at JPL to produce pupil plane and image plane coronagraph masks by combining electron beam, deep reactive ion etching, and black silicon technologies with illustrative examples of each, highlighting milestone accomplishments from the High Contrast Imaging Testbed (HCIT) at JPL and from the High Contrast Imaging Lab (HCIL) at Princeton University. We also present briefly the technologies applied to fabricate laboratory scale star shade masks.

  17. Exoplanet coronagraph shaped pupil masks and laboratory scale star shade masks: design, fabrication and characterization

    NASA Astrophysics Data System (ADS)

    Balasubramanian, Kunjithapatham; White, Victor; Yee, Karl; Echternach, Pierre; Muller, Richard; Dickie, Matthew; Cady, Eric; Mejia Prada, Camilo; Ryan, Daniel; Poberezhskiy, Ilya; Zhou, Hanying; Kern, Brian; Riggs, A. J.; Zimmerman, Neil T.; Sirbu, Dan; Shaklan, Stuart; Kasdin, Jeremy

    2015-09-01

    Star light suppression technologies to find and characterize faint exoplanets include internal coronagraph instruments as well as external star shade occulters. Currently, the NASA WFIRST-AFTA mission study includes an internal coronagraph instrument to find and characterize exoplanets. Various types of masks could be employed to suppress the host star light to about 10-9 level contrast over a broad spectrum to enable the coronagraph mission objectives. Such masks for high contrast internal coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultra-low reflectivity regions, uniformity, wave front quality, achromaticity, etc. We present the approaches employed at JPL to produce pupil plane and image plane coronagraph masks by combining electron beam, deep reactive ion etching, and black silicon technologies with illustrative examples of each, highlighting milestone accomplishments from the High Contrast Imaging Testbed (HCIT) at JPL and from the High Contrast Imaging Lab (HCIL) at Princeton University. We also present briefly the technologies applied to fabricate laboratory scale star shade masks.

  18. Facile 3D Metal Electrode Fabrication for Energy Applications via Inkjet Printing and Shape Memory Polymer

    NASA Astrophysics Data System (ADS)

    Roberts, R. C.; Wu, J.; Hau, N. Y.; Chang, Y. H.; Feng, S. P.; Li, D. C.

    2014-11-01

    This paper reports on a simple 3D metal electrode fabrication technique via inkjet printing onto a thermally contracting shape memory polymer (SMP) substrate. Inkjet printing allows for the direct patterning of structures from metal nanoparticle bearing liquid inks. After deposition, these inks require thermal curing steps to render a stable conductive film. By printing onto a SMP substrate, the metal nanoparticle ink can be cured and substrate shrunk simultaneously to create 3D metal microstructures, forming a large surface area topology well suited for energy applications. Polystyrene SMP shrinkage was characterized in a laboratory oven from 150-240°C, resulting in a size reduction of 1.97-2.58. Silver nanoparticle ink was patterned into electrodes, shrunk, and the topology characterized using scanning electron microscopy. Zinc-Silver Oxide microbatteries were fabricated to demonstrate the 3D electrodes compared to planar references. Characterization was performed using 10M potassium hydroxide electrolyte solution doped with zinc oxide (57g/L). After a 300s oxidation at 3Vdc, the 3D electrode battery demonstrated a 125% increased capacity over the reference cell. Reference cells degraded with longer oxidations, but the 3D electrodes were fully oxidized for 4 hours, and exhibited a capacity of 5.5mA-hr/cm2 with stable metal performance.

  19. Fabrication and Characterization of Nitinol-Copper Shape Memory Alloy Bimorph Actuators

    NASA Astrophysics Data System (ADS)

    Wongweerayoot, E.; Srituravanich, W.; Pimpin, A.

    2015-02-01

    This study aims to examine the effect of annealing conditions on nitinol (NiTi) characteristics and applies this knowledge to fabricate a NiTi-copper shape memory alloy bimorph actuator. The effect of the annealing conditions was investigated at various temperatures, i.e., 500, 600, and 650 °C, for 30 min. With the characterizations using x-ray diffraction, energy dispersive spectroscopy, and differential scanning calorimetry techniques, the results showed that annealing temperatures at 600 and 650 °C were able to appropriately form the crystalline structure of NiTi. However, at these high annealing temperatures, the oxide on a surface was unavoidable. In the fabrication of actuator, the annealing at 650 °C for 30 min was chosen, and it was performed at two pre-stressing conditions, i.e., straight and curved molds. From static and dynamic response experiments, the results suggested that the annealing temperature significantly affected the deflection of the actuator. On the other hand, the effect of pre-stressing conditions was relatively small. Furthermore, the micro gripper consisting of two NiTi-copper bimorph actuators successfully demonstrated for the viability of small object manipulation as the gripper was able to grasp and hold a small plastic ball with its weight of around 0.5 mg.

  20. Near-Net Shape Fabrication Using Low-Cost Titanium Alloy Powders

    SciTech Connect

    Dr. David M. Bowden; Dr. William H. Peter

    2012-03-31

    The use of titanium in commercial aircraft production has risen steadily over the last half century. The aerospace industry currently accounts for 58% of the domestic titanium market. The Kroll process, which has been used for over 50 years to produce titanium metal from its mineral form, consumes large quantities of energy. And, methods used to convert the titanium sponge output of the Kroll process into useful mill products also require significant energy resources. These traditional approaches result in product forms that are very expensive, have long lead times of up to a year or more, and require costly operations to fabricate finished parts. Given the increasing role of titanium in commercial aircraft, new titanium technologies are needed to create a more sustainable manufacturing strategy that consumes less energy, requires less material, and significantly reduces material and fabrication costs. A number of emerging processes are under development which could lead to a breakthrough in extraction technology. Several of these processes produce titanium alloy powder as a product. The availability of low-cost titanium powders may in turn enable a more efficient approach to the manufacture of titanium components using powder metallurgical processing. The objective of this project was to define energy-efficient strategies for manufacturing large-scale titanium structures using these low-cost powders as the starting material. Strategies include approaches to powder consolidation to achieve fully dense mill products, and joining technologies such as friction and laser welding to combine those mill products into near net shape (NNS) preforms for machining. The near net shape approach reduces material and machining requirements providing for improved affordability of titanium structures. Energy and cost modeling was used to define those approaches that offer the largest energy savings together with the economic benefits needed to drive implementation. Technical

  1. Glass-on-Glass Fabrication of Bottle-Shaped Tunable Microlasers and their Applications

    PubMed Central

    Ward, Jonathan M.; Yang, Yong; Nic Chormaic, Síle

    2016-01-01

    We describe a novel method for making microbottle-shaped lasers by using a CO2 laser to melt Er:Yb glass onto silica microcapillaries or fibres. This is realised by the fact that the two glasses have different melting points. The CO2 laser power is controlled to flow the doped glass around the silica cylinder. In the case of a capillary, the resulting geometry is a hollow, microbottle-shaped resonator. This is a simple method for fabricating a number of glass whispering gallery mode (WGM) lasers with a wide range of sizes on a single, micron-scale structure. The Er:Yb doped glass outer layer is pumped at 980 nm via a tapered optical fibre and WGM lasing is recorded around 1535 nm. This structure facilitates a new way to thermo-optically tune the microlaser modes by passing gas through the capillary. The cooling effect of the gas flow shifts the WGMs towards shorter wavelengths and thermal tuning of the lasing modes over 70 GHz is achieved. Results are fitted using the theory of hot wire anemometry, allowing the flow rate to be calibrated with a flow sensitivity as high as 72 GHz/sccm. Strain tuning of the microlaser modes by up to 60 GHz is also demonstrated. PMID:27121151

  2. Fabrication and lithium storage performance of sugar apple-shaped SiOx@C nanocomposite spheres

    NASA Astrophysics Data System (ADS)

    Li, Mingqi; Zeng, Ying; Ren, Yurong; Zeng, Chunmei; Gu, Jingwei; Feng, Xiaofang; He, Hongyan

    2015-08-01

    Nonstoichiometric SiOx is a kind of very attractive anode material for high-energy lithium-ion batteries because of a high specific capacity and facile synthesis. However, the poor electrical conductivity and unstable electrode structure of SiOx severely limit its electrochemical performance as anode in lithium-ion batteries. In this work, highly durable sugar apple-shaped SiOx@C nanocomposite spheres are fabricated to achieve significantly improved electrochemical performance. The composite is synthesized by homogenous one-pot synthesis, using ethyltriethoxysilanes (EtSi(OEt)3) and resorcinol/formaldehyde (RF) as starting materials. The morphology, composition and structure of the composite are investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), elemental analysis (EA) and X-ray photoelectron spectroscopy (XPS). At a current density of 50 mA g-1, the sugar apple-shaped SiOx@C spheres exhibit a stable discharge capacity of about 630 mAh g-1 calculated on the total mass of both SiOx and C. At a current density of 100 mA g-1, a stable discharge capacity of about 550 mAh g-1 is obtained and the capacity has been kept up to 400 cycles. The excellent cycling performance is attributed to the homogeneous dispersion of SiOx in disordered carbon at the nanometer scale and the unique structure of the composite.

  3. Glass-on-Glass Fabrication of Bottle-Shaped Tunable Microlasers and their Applications.

    PubMed

    Ward, Jonathan M; Yang, Yong; Nic Chormaic, Síle

    2016-04-28

    We describe a novel method for making microbottle-shaped lasers by using a CO2 laser to melt Er:Yb glass onto silica microcapillaries or fibres. This is realised by the fact that the two glasses have different melting points. The CO2 laser power is controlled to flow the doped glass around the silica cylinder. In the case of a capillary, the resulting geometry is a hollow, microbottle-shaped resonator. This is a simple method for fabricating a number of glass whispering gallery mode (WGM) lasers with a wide range of sizes on a single, micron-scale structure. The Er:Yb doped glass outer layer is pumped at 980 nm via a tapered optical fibre and WGM lasing is recorded around 1535 nm. This structure facilitates a new way to thermo-optically tune the microlaser modes by passing gas through the capillary. The cooling effect of the gas flow shifts the WGMs towards shorter wavelengths and thermal tuning of the lasing modes over 70 GHz is achieved. Results are fitted using the theory of hot wire anemometry, allowing the flow rate to be calibrated with a flow sensitivity as high as 72 GHz/sccm. Strain tuning of the microlaser modes by up to 60 GHz is also demonstrated.

  4. Glass-on-Glass Fabrication of Bottle-Shaped Tunable Microlasers and their Applications

    NASA Astrophysics Data System (ADS)

    Ward, Jonathan M.; Yang, Yong; Nic Chormaic, Síle

    2016-04-01

    We describe a novel method for making microbottle-shaped lasers by using a CO2 laser to melt Er:Yb glass onto silica microcapillaries or fibres. This is realised by the fact that the two glasses have different melting points. The CO2 laser power is controlled to flow the doped glass around the silica cylinder. In the case of a capillary, the resulting geometry is a hollow, microbottle-shaped resonator. This is a simple method for fabricating a number of glass whispering gallery mode (WGM) lasers with a wide range of sizes on a single, micron-scale structure. The Er:Yb doped glass outer layer is pumped at 980 nm via a tapered optical fibre and WGM lasing is recorded around 1535 nm. This structure facilitates a new way to thermo-optically tune the microlaser modes by passing gas through the capillary. The cooling effect of the gas flow shifts the WGMs towards shorter wavelengths and thermal tuning of the lasing modes over 70 GHz is achieved. Results are fitted using the theory of hot wire anemometry, allowing the flow rate to be calibrated with a flow sensitivity as high as 72 GHz/sccm. Strain tuning of the microlaser modes by up to 60 GHz is also demonstrated.

  5. An innovative method and experiment for fabricating bulgy shape nanochannel using AFM

    NASA Astrophysics Data System (ADS)

    Lin, Zone-Ching; Jheng, Hao-Yuan; Ding, Hao-Yang

    2015-08-01

    The paper proposes using atomic force microscopy (AFM) and the concept of specific down force energy (SDFE) to establish an innovative offset cycle cutting method for fabricating a bulgy shape nanochannel on a single-crystal silicon substrate. In the offset cycle cutting method, cutting is performed at a constant down force in all cutting passes. After the first cutting pass, the AFM probe is offset rightward for the second pass and subsequently offset leftward to the middle (i.e., between the positions of the first two cutting passes) for the third cutting pass. Applying a step-by-step method to modify the offset distance and approach the defined SDFE value, this study determined the depth of the middle cutting pass and smaller values of upward bulginess and downward indentation at the bottom of the nanochannel. The nanochannel width can be increased by increasing the number of offset cycle cutting passes. In addition, by applying the proposed method, this study involved a simulation and experiment concerning the cutting path plan of bulgy shape nanochannels. Furthermore, using a small down force along the burr path is proposed for reducing burr height. The results of the simulation and experiment were compared to verify the feasibility of the method.

  6. Convoluted accommodation structures in folded rocks

    NASA Astrophysics Data System (ADS)

    Dodwell, T. J.; Hunt, G. W.

    2012-10-01

    A simplified variational model for the formation of convoluted accommodation structures, as seen in the hinge zones of larger-scale geological folds, is presented. The model encapsulates some important and intriguing nonlinear features, notably: infinite critical loads, formation of plastic hinges, and buckling on different length-scales. An inextensible elastic beam is forced by uniform overburden pressure and axial load into a V-shaped geometry dictated by formation of a plastic hinge. Using variational methods developed by Dodwell et al., upon which this paper leans heavily, energy minimisation leads to representation as a fourth-order nonlinear differential equation with free boundary conditions. Equilibrium solutions are found using numerical shooting techniques. Under the Maxwell stability criterion, it is recognised that global energy minimisers can exist with convoluted physical shapes. For such solutions, parallels can be drawn with some of the accommodation structures seen in exposed escarpments of real geological folds.

  7. A fabrication method of unique Nafion shapes by painting for ionic polymer-metal composites (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Trabia, Sarah; Hwang, Taeseon; Kim, Kwang Jin

    2016-04-01

    Ionic Polymer-Metal Composites (IPMC) are useful actuators because of their ability to be fabricated in different shapes and move in various ways. However, the process to produce an IPMC is complicated and takes a few days. To make it possible to mass produce in any desired shape, the fabrication process must be updated. Presented here is a new way of producing the Nafion® base through a spraying method, then the electrode will be plated with spraying method as well. To verify that this method of fabrication produces a Nafion® sample similar to that which is commercially available, a sample that was made using spraying method and N117 purchased from DuPont™ were tested for various characteristics and compared.

  8. Determination of collisional linewidths and shifts by a convolution method

    NASA Technical Reports Server (NTRS)

    Pickett, H. M.

    1980-01-01

    A technique is described for fitting collisional linewidths and shifts from experimental spectral data. The method involves convoluting a low-pressure reference spectrum with a Lorentz shape function and comparing the convoluted spectrum with higher pressure spectra. Several experimental examples are given. One advantage of the method is that no extra information is needed about the instrument response function or spectral modulation. In addition, the method is shown to be relatively insensitive to the presence of reflections in the sample cell.

  9. Strategy for Fabricating Multiple-Shape-Memory Polymeric Materials via the Multilayer Assembly of Co-Continuous Blends.

    PubMed

    Zheng, Yu; Ji, Xiaoying; Yin, Min; Shen, Jiabin; Guo, Shaoyun

    2017-09-05

    Shape-memory polymeric materials containing alternating layers of thermoplastic polyurethane (TPU) and co-continuous poly(butylene succinate) (PBS)/polycaprolactone (PCL) blends (denoted SLBs) were fabricated through layer-multiplying coextrusion. Because there were two well-separated phase transitions caused by the melt of PCL and PBS, both the dual- and triple-shape-memory effects were discussed. Compared with the blending specimen with the same components, the TPU/SLB multilayer system with a multicontinuous structure and a plenty of layer interfaces was demonstrated to have higher shape fixity and recovery ability. When the number of layers reached 128, both the shape fixity and recovery ratios were beyond 95 and 85% in dual- and triple-shape-memory processes, respectively, which were difficult to be achieved through conventional melt-processing methods. On the basis of the classic viscoelastic theory, the parallel-assembled TPU and SLB layers capable of maintaining the same strain along the deforming direction were regarded to possess the maximum ability to fix temporary shapes and trigger them to recover back to original ones through the interfacial shearing effect. Accordingly, the present approach provided an efficient strategy for fabricating outstanding multiple-shape-memory polymers, which may exhibit a promising application in the fields of biomedical devices, sensors and actuators, and so forth.

  10. Fabrication and surface photovoltage study of hematite microparticles with hollow spindle-shaped structure

    NASA Astrophysics Data System (ADS)

    Li, Hong; Zhao, Qidong; Li, Xinyong; Shi, Yong; Chen, Guohua

    2012-07-01

    Hematite (α-Fe2O3) particles with hollow spindle-shaped microstructure were successfully synthesized by a one-pot hydrothermal approach in large scale. The structural properties of the sample were systematically investigated by X-ray powder diffraction, scanning electron microscopy, energy-dispersive X-ray spectrum, high resolution transmission electron microscopy, selected-area electron diffraction techniques, UV-vis diffuse reflectance spectroscopy and infrared spectroscopy techniques. The characterization results revealed that the α-Fe2O3 microparticles with a single-domain crystalline structure was mainly grown along the (1 0 4) crystal plane. The valence states and the surface chemical compositions of α-Fe2O3 were further identified by X-ray photoelectron spectroscopy. The feature of photo-induced charge separation on spectrum was demonstrated by the surface photovoltage measurement under different external biases. The observed photoelectric characteristics of the as-fabricated material are beneficial for various optical and electronic applications.

  11. Fabrication of a bowl-shaped silver cavity substrate for SERS-based immunoassay.

    PubMed

    Tian, Shu; Zhou, Qun; Gu, Zhuomin; Gu, Xuefang; Zheng, Junwei

    2013-05-07

    In this study, a metal sandwich substrate bridged by an immunocomplex has been created for a surface enhanced Raman scattering (SERS)-based immunoassay. The bottom bowl-shaped silver cavity thin film layer was prepared by electrodeposition using a closely packed monolayer of 700 nm diameter polystyrene spheres as a template. The reflection spectra of the films were recorded as a function of film thickness, and then correlated with SERS enhancement using p-aminothiophenol as the probe molecule. The results demonstrate that SERS enhancement can be maximized when both the frequency of the incident laser and Raman scattering approach the resonance frequency of the localized surface plasmon resonance, providing a guideline for the fabrication and further application of these nanocavity arrays. The second layer of silver was introduced by the interactions between the immunocomplexes in the middle layer of the sandwich architecture and the silver nanoparticles. The proposed structure was used to perform the SERS-based immunoassay. The labeled protein can be detected over a wide concentration range and the detection limit of TRITC and Atto610 labeled proteins were 50 and 5 pg mL(-1), respectively. The results demonstrate that the new SERS substrate is suitable for the quantitative identification of biomolecules.

  12. Experimental characterisation of PD SOI MOSFET devices fabricated with diamond-shaped body contact

    NASA Astrophysics Data System (ADS)

    Daghighi, Arash; Osman, Mohamed A.

    2011-06-01

    The design of diamond-shaped body-contacted (DSBC) devices using standard layers in a 0.35 µm silicon-on-insulator (SOI) complementary metal-oxide-semiconductor process is described in this article. The technology is based on a manufacturable partially depleted SOI process targeted for radio frequency applications. The experimental measurements of drain induced barrier lowering for the fabricated DSBC structure showed suppression of floating body effects (FBE) at the promising rate of 24 mV/V. The measurement results confirmed current drive (I DS) improvement by 25% at V DS = 1.5 V and V GS = 1.5 V compared to conventional body-tied-source (BTS) device. A constant and steady output conductance (g DS) in the saturation region was observed for the DSBC structure. The gate trans-conductance (g m) is improved by 34% at V DS = 1.5 V and V GS = 1.5 V compared to conventional BTS device. Three-dimensional device simulation provides insight on FBE suppression and channel current improvement. Experimental results confirmed the area efficiency of the DSBC structure and its excellent current drive performance.

  13. A Novel Shape Memory Alloy Annuloplasty Ring for Minimally Invasive Surgery: Design, Fabrication, and Evaluation

    PubMed Central

    Purser, Molly F.; Richards, Andrew L.; Cook, Richard C.; Osborne, Jason A.; Cormier, Denis R.; Buckner, Gregory D.

    2013-01-01

    A novel annuloplasty ring with a shape memory alloy core has been developed to facilitate minimally invasive mitral valve repair. In its activated (austenitic) phase, this prototype ring has comparable mechanical properties to commercial semi-rigid rings. In its pre-activated (martensitic) phase, this ring is flexible enough to be introduced through an 8-mm trocar and easily manipulated with robotic instruments within the confines of a left atrial model. The core is constructed of 0.50 mm diameter NiTi, which is maintained below its martensitic transition temperature (24 °C) during deployment and suturing. After suturing, the ring is heated above its austenitic transition temperature (37 °C, normal human body temperature) enabling the NiTi core to attain its optimal geometry and stiffness characteristics indefinitely. This article summarizes the design, fabrication, and evaluation of this prototype ring. Experimental results suggest that the NiTi core ring could be a viable alternative to flexible bands in robot-assisted minimally invasive mitral valve repair. PMID:20652747

  14. Polarization-independent etching of fused silica based on electrons dynamics control by shaped femtosecond pulse trains for microchannel fabrication.

    PubMed

    Yan, X; Jiang, L; Li, X; Zhang, K; Xia, B; Liu, P; Qu, L; Lu, Y

    2014-09-01

    We propose an approach to realize polarization-independent etching of fused silica by using temporally shaped femtosecond pulse trains to control the localized transient electrons dynamics. Instead of nanograting formation using traditional unshaped pulses, for the pulse delay of pulse trains larger than 1 ps, coherent field-vector-related coupling is not possible and field orientation is lost. The exponential growth of the periodic structures is interrupted. In this case, disordered and interconnected nanostructures are formed, which is probably the main reason of etching independence on the laser polarization. As an application example, square-wave-shaped and arc-shaped microchannels are fabricated by using pulse trains to demonstrate the advantage of the proposed method in fabricating high-aspect-ratio and three-dimensional microchannels.

  15. Fabrication of 10 nm-scale complex 3D nanopatterns with multiple shapes and components by secondary sputtering phenomenon.

    PubMed

    Jeon, Hwan-Jin; Jeong, Hyeon Su; Kim, Yun Ho; Jung, Woo-Bin; Kim, Jeong Yeon; Jung, Hee-Tae

    2014-02-25

    We introduce an advanced ultrahigh-resolution (∼ 15 nm) patterning technique that enables the fabrication of various 3D high aspect ratio multicomponents/shaped nanostructures. This methodology utilizes the repetitive secondary sputtering phenomenon under etching plasma conditions and prepatterned fabrication control. The secondary sputtering phenomenon repetitively generates an angular distribution of target particles during ion-bombardment. This method, advanced repetitive secondary sputtering lithography, provides many strategies to fabricate complex continuous patterns and multilayer/material patterns with 10 nm-scale resolution. To demonstrate the versatility of this method, we show induced vertical alignment of liquid crystals (LCs) on indium-tin-oxide (ITO) grid patterns without any alignment layers. The ITO grid pattern fabricated in this method is found to have not only an alignment capability but also electrode properties without electrical or optical damage.

  16. Understanding deep convolutional networks

    PubMed Central

    Mallat, Stéphane

    2016-01-01

    Deep convolutional networks provide state-of-the-art classifications and regressions results over many high-dimensional problems. We review their architecture, which scatters data with a cascade of linear filter weights and nonlinearities. A mathematical framework is introduced to analyse their properties. Computations of invariants involve multiscale contractions with wavelets, the linearization of hierarchical symmetries and sparse separations. Applications are discussed. PMID:26953183

  17. Melt-spun shaped fibers with enhanced surface effects: fiber fabrication, characterization and application to woven scaffolds.

    PubMed

    Park, S J; Lee, B-K; Na, M H; Kim, D S

    2013-08-01

    Scaffolds with a high surface-area-to-volume ratio (SA:V) are advantageous with regard to the attachment and proliferation of cells in the field of tissue engineering. This paper reports on the development of novel melt-spun fibers with a high SA:V, which enhanced the surface effects of a fiber-based scaffold while maintaining its mechanical strength. The cross-section of the fibers was altered to a non-circular shape, producing a higher SA:V for a similar cross-sectional area. To obtain fibers with non-circular cross-sectional shape, or shaped fibers, three different types of metal spinnerets were fabricated for the melt-spinning process, each with circular, triangular or cruciform capillaries, using deep X-ray lithography followed by nickel electroforming. Using these spinnerets, circular and shaped fibers were manufactured with biodegradable polyester, polycaprolactone. The SA:V increase in the shaped fibers was experimentally investigated under different processing conditions. Tensile tests on the fibers and indentation tests on the woven fiber scaffolds were performed. The tested fibers and scaffolds exhibited similar mechanical characteristics, due to the similar cross-sectional area of the fibers. The degradation of the shaped fibers was notably faster than that of circular fibers, because of the enlarged surface area of the shaped fibers. The woven scaffolds composed of the shaped fibers significantly increased the proliferation of human osteosarcoma MG63 cells. This approach to increase the SA:V in shaped fibers could be useful for the fabrication of programmable, biodegradable fiber-based scaffolds in tissue engineering.

  18. Convolution of degrees of coherence.

    PubMed

    Korotkova, Olga; Mei, Zhangrong

    2015-07-01

    The conditions under which convolution of two degrees of coherence represents a novel legitimate degree of coherence are established for wide-sense statistically stationary Schell-model beam-like optical fields. Several examples are given to illustrate how convolution can be used for generation of a far field being a modulated version of another one. Practically, the convolutions of the degrees of coherence can be achieved by programming the liquid crystal spatial light modulators.

  19. Fabrication of volcano-shaped nano-patterned sapphire substrates using colloidal self-assembly and wet chemical etching.

    PubMed

    Geng, Chong; Zheng, Lu; Fang, Huajing; Yan, Qingfeng; Wei, Tongbo; Hao, Zhibiao; Wang, Xiaoqing; Shen, Dezhong

    2013-08-23

    Patterned sapphire substrates (PSS) have been widely used to enhance the light output power in GaN-based light emitting diodes. The shape and feature size of the pattern in a PSS affect its enhancement efficiency to a great degree. In this work we demonstrate the nanoscale fabrication of volcano-shaped PSS using a wet chemical etching approach in combination with a colloidal monolayer templating strategy. Detailed analysis by scanning electron microscopy reveals that the unique pattern shape is a result of the different corrosion-resistant abilities of silica masks of different effective heights during wet chemical etching. The formation of silica etching masks of different effective heights has been ascribed to the silica precursor solution in the interstice of the colloidal monolayer template being distributed unevenly after infiltration. In the subsequent wet chemical etching process, the active reaction sites altered as etching duration was prolonged, resulting in the formation of volcano-shaped nano-patterned sapphire substrates.

  20. Novel D-shaped fiber fabrication method for saturable absorber application in the generation of ultra-short pulses

    NASA Astrophysics Data System (ADS)

    Ahmad, H.; Safaei, R.; Rezayi, M.; Amiri, I. S.

    2017-08-01

    A cost-efficient, time-saving and effective technique for the fabrication of D-shaped fibers is presented, to provide a platform with a strong evanescent field to be used as a saturable absorber (SA). This technique provides flexibility by removing the required portion of the fiber, and a small polished length which offers a unique opportunity to deposit SA on its surface by simply submerging it in the SA solution without high losses. A compact fiber laser utilizing a graphene oxide coating on a fabricated D-shaped fiber as an SA capable of generating ultrashort pulses is designed and verified. We report the generation of ultrafast pulses as short as 227 fs with a 34.7 MHz repetition rate, having a 3 dB bandwidth of 14 nm at the 1570 nm center wavelength.

  1. Slit beam shaping method for femtosecond laser direct-write fabrication of symmetric waveguides in bulk glasses

    NASA Astrophysics Data System (ADS)

    Ams, Martin; Marshall, G. D.; Spence, D. J.; Withford, M. J.

    2005-07-01

    We report both theoretical and experimental results of a slit beam shaping configuration for fabricating photonic waveguides by use of femtosecond laser pulses. Most importantly we show the method supports focusing objectives with a long depth of field and allows the direct-writing of microstructures with circular cross-sections whilst employing a perpendicular writing scheme. We applied this technique to write low loss (0.39 dB/cm), single mode waveguides in phosphate glass.

  2. Convolutional coding techniques for data protection

    NASA Technical Reports Server (NTRS)

    Massey, J. L.

    1975-01-01

    Results of research on the use of convolutional codes in data communications are presented. Convolutional coding fundamentals are discussed along with modulation and coding interaction. Concatenated coding systems and data compression with convolutional codes are described.

  3. Shape-controlled fabrication of cell-laden calcium alginate-PLL hydrogel microcapsules by electrodeposition on microelectrode.

    PubMed

    Chen, Weinan; Zhu, Bowen; Ma, Li; Hua, Xiaoqing

    2017-10-01

    In this study, we propose an electrodeposition method of fabricating shape-controlled calcium alginate-poly-L-lysine hydrogel microcapsules. The micro-patterned electrodes, which are produced by coating a patterned photoresist layer onto fluorine-doped tin oxide glass slide based on photolithography technique, are used for making different shapes of microcapsules. By the electrolysis of water in alginate gelation on micro-patterned anode electrode, the 2D alginate hydrogel structures embedded with yeast cells are formed on fluorine-doped tin oxide glass slide. Then, the 2D structures would be detached from the microelectrode surface and treated with given reagent to be transformed into 3D microcapsules while maintaining the ring and hexagon shapes. Finally, the yeast cells within the microcapsules are further promoted into compact tissues by cultivation. The experimental results indicate the method can successfully fabricate tissues which can maintain certain cells bioactivity after 24 h cultivation. The recommended method can lead to fabricating cell-laden scaffold for tissue engineering, biological studies and drug discovery with higher accuracy and efficiency.

  4. Fabrication of petal-shaped masks for suppression of the on-axis Poisson spot in telescope systems.

    PubMed

    Shiri, Ron; Stein, Ryan; Murphy, Kaitlin; Hagopian, Kimberly; Salari, Shirin; Sankar, Shannon; Hagopian, John; Showalter, Matthew; Stevenson, Thomas; Quijada, Manuel; Threat, Felix; Friedlander, Jay; Dillon, Thomas; Livas, Jeffrey

    2016-04-01

    The presence of a bright (Poisson) spot in the geometrical shadow of circular/spherical shapes has been known for the past two centuries. A broad class of telescopes that involve simultaneous transmit and receive require suppression of the reflected light from the secondary mirror on the detector. For instance, the on-axis design of optical telescope for the evolved Laser Interferometric Space Antenna (eLISA), a re-scoped version of the baseline LISA mission concept, requires suppression of reflected laser light from the secondary mirror on the detector. In the past few years, the hypergaussian functions with petal-shaped realization have been shown to significantly suppress intensity along the optical axis. This work reports on fabrication of a series of petal-shaped masks using a variety of techniques such as 3D printing, photolithography, and wire Electro Discharge Machining. These masks are designed and fabricated to operate in the range of Fresnel numbers between 4 and 120. This paper discusses the challenges, successes, and failures of each fabrication technique and the optical performance of typical masks with suggestions for potential follow up work.

  5. Fabrication of petal-shaped masks for suppression of the on-axis Poisson spot in telescope systems

    NASA Astrophysics Data System (ADS)

    Shiri, Ron; Stein, Ryan; Murphy, Kaitlin; Hagopian, Kimberly; Salari, Shirin; Sankar, Shannon; Hagopian, John; Showalter, Matthew; Stevenson, Thomas; Quijada, Manuel; Threat, Felix; Friedlander, Jay; Dillon, Thomas; Livas, Jeffrey

    2016-04-01

    The presence of a bright (Poisson) spot in the geometrical shadow of circular/spherical shapes has been known for the past two centuries. A broad class of telescopes that involve simultaneous transmit and receive require suppression of the reflected light from the secondary mirror on the detector. For instance, the on-axis design of optical telescope for the evolved Laser Interferometric Space Antenna (eLISA), a re-scoped version of the baseline LISA mission concept, requires suppression of reflected laser light from the secondary mirror on the detector. In the past few years, the hypergaussian functions with petal-shaped realization have been shown to significantly suppress intensity along the optical axis. This work reports on fabrication of a series of petal-shaped masks using a variety of techniques such as 3D printing, photolithography, and wire Electro Discharge Machining. These masks are designed and fabricated to operate in the range of Fresnel numbers between 4 and 120. This paper discusses the challenges, successes, and failures of each fabrication technique and the optical performance of typical masks with suggestions for potential follow up work.

  6. Progress in net shape fabrication of alpha SiC turbine components

    SciTech Connect

    Storm, R.S.; Naum, R.G.

    1983-01-01

    An update on the status of ceramic component development in the AGT and CATE Programs is presented. Activity on the DDA AGT Program has focused on injection molded rotors in addition to static components. Fabrication of components for the Garrett AGT Program emphasized the very large injection molded turbine shroud and injection molded interchangeable segmented stator as well as slip cast and isopressed components. The fabrication aspect of the CATE Turbine Blade Optimization Program is also reviewed.

  7. Effect of fabrication-dependent shape and composition of solid-state nanopores on single nanoparticle detection.

    PubMed

    Liu, Shuo; Yuzvinsky, Thomas D; Schmidt, Holger

    2013-06-25

    Solid-state nanopores can be fabricated in a variety of ways and form the basis for label-free sensing of single nanoparticles: as individual nanoparticles traverse the nanopore, they alter the ionic current across it in a characteristic way. Typically, nanopores are described by the diameter of their limiting aperture, and less attention has been paid to other, fabrication-dependent parameters. Here, we report a comprehensive analysis of the properties and sensing performance of three types of nanopore with identical 50 nm aperture, but fabricated using three different techniques: direct ion beam milling, ion beam sculpting, and electron beam sculpting. The nanopores differ substantially in physical shape and chemical composition as identified by ion-beam assisted cross-sectioning and energy dispersive X-ray spectroscopy. Concomitant differences in electrical sensing of single 30 nm beads, such as variations in blockade depth, duration, and electric field dependence, are observed and modeled using hydrodynamic simulations. The excellent agreement between experiment and physical modeling shows that the physical properties (shape) and not the chemical surface composition determine the sensing performance of a solid-state nanopore in the absence of deliberate surface modification. Consequently, nanoparticle sensing performance can be accurately predicted once the full three-dimensional structure of the nanopore is known.

  8. Fabrication and characterization of a micromachined swirl-shaped ionic polymer metal composite actuator with electrodes exhibiting asymmetric resistance.

    PubMed

    Feng, Guo-Hua; Liu, Kim-Min

    2014-05-12

    This paper presents a swirl-shaped microfeatured ionic polymer-metal composite (IPMC) actuator. A novel micromachining process was developed to fabricate an array of IPMC actuators on a glass substrate and to ensure that no shortcircuits occur between the electrodes of the actuator. We demonstrated a microfluidic scheme in which surface tension was used to construct swirl-shaped planar IPMC devices of microfeature size and investigated the flow velocity of Nafion solutions, which formed the backbone polymer of the actuator, within the microchannel. The unique fabrication process yielded top and bottom electrodes that exhibited asymmetric surface resistance. A tool for measuring surface resistance was developed and used to characterize the resistances of the electrodes for the fabricated IPMC device. The actuator, which featured asymmetric electrode resistance, caused a nonzero-bias current when the device was driven using a zero-bias square wave, and we propose a circuit model to describe this phenomenon. Moreover, we discovered and characterized a bending and rotating motion when the IPMC actuator was driven using a square wave. We observed a strain rate of 14.6% and a displacement of 700 μm in the direction perpendicular to the electrode surfaces during 4.5-V actuation.

  9. Fabrication and Characterization of a Micromachined Swirl-Shaped Ionic Polymer Metal Composite Actuator with Electrodes Exhibiting Asymmetric Resistance

    PubMed Central

    Feng, Guo-Hua; Liu, Kim-Min

    2014-01-01

    This paper presents a swirl-shaped microfeatured ionic polymer-metal composite (IPMC) actuator. A novel micromachining process was developed to fabricate an array of IPMC actuators on a glass substrate and to ensure that no shortcircuits occur between the electrodes of the actuator. We demonstrated a microfluidic scheme in which surface tension was used to construct swirl-shaped planar IPMC devices of microfeature size and investigated the flow velocity of Nafion solutions, which formed the backbone polymer of the actuator, within the microchannel. The unique fabrication process yielded top and bottom electrodes that exhibited asymmetric surface resistance. A tool for measuring surface resistance was developed and used to characterize the resistances of the electrodes for the fabricated IPMC device. The actuator, which featured asymmetric electrode resistance, caused a nonzero-bias current when the device was driven using a zero-bias square wave, and we propose a circuit model to describe this phenomenon. Moreover, we discovered and characterized a bending and rotating motion when the IPMC actuator was driven using a square wave. We observed a strain rate of 14.6% and a displacement of 700 μm in the direction perpendicular to the electrode surfaces during 4.5-V actuation. PMID:24824370

  10. Dealiased convolutions for pseudospectral simulations

    NASA Astrophysics Data System (ADS)

    Roberts, Malcolm; Bowman, John C.

    2011-12-01

    Efficient algorithms have recently been developed for calculating dealiased linear convolution sums without the expense of conventional zero-padding or phase-shift techniques. For one-dimensional in-place convolutions, the memory requirements are identical with the zero-padding technique, with the important distinction that the additional work memory need not be contiguous with the input data. This decoupling of data and work arrays dramatically reduces the memory and computation time required to evaluate higher-dimensional in-place convolutions. The memory savings is achieved by computing the in-place Fourier transform of the data in blocks, rather than all at once. The technique also allows one to dealias the n-ary convolutions that arise on Fourier transforming cubic and higher powers. Implicitly dealiased convolutions can be built on top of state-of-the-art adaptive fast Fourier transform libraries like FFTW. Vectorized multidimensional implementations for the complex and centered Hermitian (pseudospectral) cases have already been implemented in the open-source software FFTW++. With the advent of this library, writing a high-performance dealiased pseudospectral code for solving nonlinear partial differential equations has now become a relatively straightforward exercise. New theoretical estimates of computational complexity and memory use are provided, including corrected timing results for 3D pruned convolutions and further consideration of higher-order convolutions.

  11. "Fabrication of arbitrarily shaped carbonate apatite foam based on the interlocking process of dicalcium hydrogen phosphate dihydrate".

    PubMed

    Sugiura, Yuki; Tsuru, Kanji; Ishikawa, Kunio

    2017-08-01

    Carbonate apatite (CO3Ap) foam with an interconnected porous structure is highly attractive as a scaffold for bone replacement. In this study, arbitrarily shaped CO3Ap foam was formed from α-tricalcium phosphate (α-TCP) foam granules via a two-step process involving treatment with acidic calcium phosphate solution followed by hydrothermal treatment with NaHCO3. The treatment with acidic calcium phosphate solution, which is key to fabricating arbitrarily shaped CO3Ap foam, enables dicalcium hydrogen phosphate dihydrate (DCPD) crystals to form on the α-TCP foam granules. The generated DCPD crystals cause the α-TCP granules to interlock with each other, inducing an α-TCP/DCPD foam. The interlocking structure containing DCPD crystals can survive hydrothermal treatment with NaHCO3. The arbitrarily shaped CO3Ap foam was fabricated from the α-TCP/DCPD foam via hydrothermal treatment at 200 °C for 24 h in the presence of a large amount of NaHCO3.

  12. Determinate-state convolutional codes

    NASA Technical Reports Server (NTRS)

    Collins, O.; Hizlan, M.

    1991-01-01

    A determinate state convolutional code is formed from a conventional convolutional code by pruning away some of the possible state transitions in the decoding trellis. The type of staged power transfer used in determinate state convolutional codes proves to be an extremely efficient way of enhancing the performance of a concatenated coding system. The decoder complexity is analyzed along with free distances of these new codes and extensive simulation results is provided of their performance at the low signal to noise ratios where a real communication system would operate. Concise, practical examples are provided.

  13. Fabrication and characterization of TiO2 coated cone shaped nano-fiber pH sensor

    NASA Astrophysics Data System (ADS)

    Pathak, A. K.; Bhardwaj, V.; Gangwar, R. K.; De, M.; Singh, V. K.

    2017-03-01

    In the present paper a novel cone shaped nano-fiber (CSNF) pH sensor using multi-mode fiber (MMF) has been fabricated and demonstrated. Three different pH indicators, chlorophenol red, bromothymol blue and cresol red with precursor tetraethyl orthosilicate (TEOS) have been used for fabrication of pH sensing layer. A significant enhancement in sensing properties of pH sensor with TiO2 thin film has been observed. The pH sensor with TiO2 thin film shows the quite high sensitivity (1.16 dBm/pH) as compared to sensor with simple pH coating (0.81 dBm/pH) at 1550 nm with a good linear response. Moreover, the sensor with TiO2 film exhibits fast response time of ∼ 25 s for pH values ranging from 4 to 11 with excellent stability and durability.

  14. Replicable and shape-controllable fabrication of electrospun fibrous scaffolds for tissue engineering.

    PubMed

    Cho, Seong J; Nam, Hyoryung; An, Taechang; Lim, Geunbae

    2012-12-01

    Controlling the architecture of electrospun fibers is one of the key issues in tissue engineering. This report describes a rapid and reproducible patterning method for the fabrication of an electrospun fibrous scaffold. The electrospun fibers were deposited on a patterned electrode. The patterned scaffold was fabricated using a thin insulating film between layers of this electrode. For a tissue engineering application, poly(lactic-co-glycolic acid) (PLGA), a biocompatible and biodegradable material, was electrospun. Fibroblast cells were cultured on the fibrous PLGA scaffold and the viability, morphology, and distribution of the cells were studied.

  15. Methods of fabricating a conductor assembly having a curvilinear arcuate shape

    DOEpatents

    Meinke, Rainer

    2011-08-23

    A method for manufacture of a conductor assembly along a curvilinear axis. The assembly may be of the type which, when conducting current, generates a magnetic field or in which, in the presence of a changing magnetic field, a voltage is induced. In one example, the assembly includes a structure having a curved shape extending along the axis. A surface of the structure is positioned for formation of a channel along the curved shape. The structure is rotated about a second axis. While rotating the structure, a channel is formed in the surface that results in a helical shape in the structure. The channel extends both around and along the first axis.

  16. Fabrication of a pen-shaped portable biochemical reaction system based on magnetic bead manipulation

    NASA Astrophysics Data System (ADS)

    Shikida, Mitsuhiro; Inagaki, Noriyuki; Okochi, Mina; Honda, Hiroyuki; Sato, Kazuo

    2011-06-01

    A pen-shaped platform that is similar to a mechanical pencil is proposed for producing a portable reaction system. A reaction unit, as the key component in the system, was produced by using a heat shrinkable tube. A mechanical pencil supplied by Mitsubishi Pencil Co. Ltd was used as the pen-shaped platform for driving the reaction cylinder. It was actuated using an inchworm motion. We confirmed that the magnetic beads were successfully manipulated in the droplet in the cylinder-shaped reaction units.

  17. Fabrication and static characterization of carbon-fiber-reinforced polymers with embedded NiTi shape memory wire actuators

    NASA Astrophysics Data System (ADS)

    de Araújo, C. J.; Rodrigues, L. F. A.; Coutinho Neto, J. F.; Reis, R. P. B.

    2008-12-01

    In this work, unidirectional carbon-fiber-reinforced polymers (CFRP) with embedded NiTi shape memory alloy (SMA) wire actuators were manufactured using a universal testing machine equipped with a thermally controlled chamber. Beam specimens containing cold-worked, annealed and trained NiTi SMA wires distributed along their neutral plane were fabricated. Several tests in a three-point bending mode at different constant temperatures were performed. To verify thermal buckling effects, electrical activation of the specimens was realized in a cantilevered beam mode and the influence of the SMA wire actuators on the tip deflection of the composite is demonstrated.

  18. Die and telescoping punch form convolutions in thin diaphragm

    NASA Technical Reports Server (NTRS)

    1965-01-01

    Die and punch set forms convolutions in thin dished metal diaphragm without stretching the metal too thin at sharp curvatures. The die corresponds to the metal shape to be formed, and the punch consists of elements that progressively slide against one another under the restraint of a compressed-air cushion to mate with the die.

  19. Fabrication of Ion-Shaped Anisotropic Nanoparticles and their Orientational Imaging by Second-Harmonic Generation Microscopy

    NASA Astrophysics Data System (ADS)

    Slablab, Abdallah; Isotalo, Tero J.; Mäkitalo, Jouni; Turquet, Léo; Coulon, Pierre-Eugène; Niemi, Tapio; Ulysse, Christian; Kociak, Mathieu; Mailly, Dominique; Rizza, Giancarlo; Kauranen, Martti

    2016-11-01

    Ion beam shaping is a novel and powerful tool to engineer nanocomposites with effective three-dimensional (3D) architectures. In particular, this technique offers the possibility to precisely control the size, shape and 3D orientation of metallic nanoparticles at the nanometer scale while keeping the particle volume constant. Here, we use swift heavy ions of xenon for irradiation in order to successfully fabricate nanocomposites consisting of anisotropic gold nanoparticle that are oriented in 3D and embedded in silica matrix. Furthermore, we investigate individual nanorods using a nonlinear optical microscope based on second-harmonic generation (SHG). A tightly focused linearly or radially-polarized laser beam is used to excite nanorods with different orientations. We demonstrate high sensitivity of the SHG response for these polarizations to the orientation of the nanorods. The SHG measurements are in excellent agreement with the results of numerical modeling based on the boundary element method.

  20. Fabrication of Ion-Shaped Anisotropic Nanoparticles and their Orientational Imaging by Second-Harmonic Generation Microscopy

    PubMed Central

    Slablab, Abdallah; Isotalo, Tero J.; Mäkitalo, Jouni; Turquet, Léo; Coulon, Pierre-Eugène; Niemi, Tapio; Ulysse, Christian; Kociak, Mathieu; Mailly, Dominique; Rizza, Giancarlo; Kauranen, Martti

    2016-01-01

    Ion beam shaping is a novel and powerful tool to engineer nanocomposites with effective three-dimensional (3D) architectures. In particular, this technique offers the possibility to precisely control the size, shape and 3D orientation of metallic nanoparticles at the nanometer scale while keeping the particle volume constant. Here, we use swift heavy ions of xenon for irradiation in order to successfully fabricate nanocomposites consisting of anisotropic gold nanoparticle that are oriented in 3D and embedded in silica matrix. Furthermore, we investigate individual nanorods using a nonlinear optical microscope based on second-harmonic generation (SHG). A tightly focused linearly or radially-polarized laser beam is used to excite nanorods with different orientations. We demonstrate high sensitivity of the SHG response for these polarizations to the orientation of the nanorods. The SHG measurements are in excellent agreement with the results of numerical modeling based on the boundary element method. PMID:27881838

  1. Direct Fabrication of Free-Standing MOF Superstructures with Desired Shapes by Micro-Confined Interfacial Synthesis.

    PubMed

    Kim, Jin-Oh; Min, Kyoung-Ik; Noh, Hyunwoo; Kim, Dong-Hwi; Park, Soo-Young; Kim, Dong-Pyo

    2016-06-13

    Recently, metal-organic frameworks (MOFs) with multifunctional pore chemistry have been intensively investigated for positioning the desired morphology at specific locations onto substrates for manufacturing devices. Herein, we develop a micro-confined interfacial synthesis (MIS) approach for fabrication of a variety of free-standing MOF superstructures with desired shapes. This approach for engineering MOFs provides three key features: 1) in situ synthesis of various free-standing MOF superstructures with controlled compositions, shape, and thickness using a mold membrane; 2) adding magnetic functionality into MOF superstructures by loading with Fe3 O4 nanoparticles; 3) transferring the synthesized MOF superstructural array on to flat or curved surface of various substrates. The MIS route with versatile potential opens the door for a number of new perspectives in various applications.

  2. Nanoscale nickel-titanium shape memory alloys thin films fabricated by using biased target ion beam deposition

    NASA Astrophysics Data System (ADS)

    Hou, Huilong

    Shape memory alloys offer the highest work output per unit volume among smart materials and have both high actuation stress and large recoverable strain. Miniaturization of materials and devices requires shape memory actuation which is uncompromised at a small scale. However, size effects need to be understood in order to scale shape memory actuation with the minimum size critical to device design. Controlling material quality and properties is essential in fabrication of shape memory alloys into nanometer regime. This work demonstrates a novel fabrication technique, biased target ion beam deposition (BTIBD), which uses additional adatom energy in order to fabricate high-quality nickel-titanium (NiTi) alloys thin films with nanometer thickness. These fabricated ultrathin NiTi films provide insight into the size scale dependence of shape memory functionality at nanoscale regime. BTIBD provides additional adatom energy to the growing film in order to fundamentally tailor the film growth mode for quality and properties. An independent ion beam source is customized in BTIBD to provide low-energy ions (tens of eV) during growth of films on substrates. Pure Ti and pure Ni targets are co-sputtering in BTIBD to fabricate NiTi thin films. The prepared NiTi films are continuous, and the thickness ranges from several tens to a few hundreds nanometers. The composition is controllable over the range of Ni-rich (>50.5 at% Ni), near-equiatomic, and Ti-rich (<49.5 at% Ni). The film surfaces are consistently ultra-smooth --- twice as smooth as conventional NiTi thin films fabricated by magnetron sputtering --- over all the composition ranges and over wide surface areas. The substrate/film interface is smooth and the interfacial diffusion is a minimal portion of the film thickness. Crystallographic phases and grain size in BTIBD NiTi films with thickness on the order of 100 nm are tunable via heat treatment. The as-deposited BTIBD films are amorphous. A pure B2 phase (without other

  3. Fabrication and characterization of shape memory polymers at small-scales

    NASA Astrophysics Data System (ADS)

    Wornyo, Edem

    The objective of this research is to thoroughly investigate the shape memory effect in polymers, characterize, and optimize these polymers for applications in information storage systems. Previous research effort in this field concentrated on shape memory metals for biomedical applications such as stents. Minimal work has been done on shape memory polymers; and the available work on shape memory polymers has not characterized the behaviors of this category of polymers fully. Copolymer shape memory materials based on diethylene glycol dimethacrylate (DEGDMA) crosslinker, and tert butyl acrylate (tBA) monomer are designed. The design encompasses a careful control of the backbone chemistry of the materials. Characterization methods such as dynamic mechanical analysis (DMA), differential scanning calorimetry (DSC); and novel nanoscale techniques such as atomic force microscopy (AFM), and nanoindentation are applied to this system of materials. Designed experiments are conducted on the materials to optimize spin coating conditions for thin films. Furthermore, the recovery, a key for the use of these polymeric materials for information storage, is examined in detail with respect to temperature. In sum, the overarching objectives of the proposed research are to: (i) Design shape memory polymers based on polyethylene glycol dimethacrylate (PEGDMA) and diethylene glycol dimethacrylate (DEGDMA) crosslinkers, 2-hydroxyethyl methacrylate (HEMA) and tert-butyl acrylate monomer (tBA). (ii) Utilize dynamic mechanical analysis (DMA) to comprehend the thermomechanical properties of shape memory polymers based on DEGDMA and tBA. (iii) Utilize nanoindentation and atomic force microscopy (AFM) to understand the nanoscale behavior of these SMPs, and explore the strain storage and recovery of the polymers from a deformed state. (iv) Study spin coating conditions on thin film quality with designed experiments. (iv) Apply neural networks and genetic algorithms to optimize these systems.

  4. Prototype fabrication and preliminary in vitro testing of a shape memory endovascular thrombectomy device.

    PubMed

    Small, Ward; Wilson, Thomas S; Buckley, Patrick R; Benett, William J; Loge, Jeffrey M; Hartman, Jonathan; Maitland, Duncan J

    2007-09-01

    An electromechanical microactuator comprised of shape memory polymer (SMP) and shape memory nickel-titanium alloy (nitinol) was developed and used in an endovascular thrombectomy device prototype. The microactuator maintains a straight rod shape until an applied current induces electro-resistive (Joule) heating, causing the microactuator to transform into a corkscrew shape. The straight-to-corkscrew transformation geometry was chosen to permit endovascular delivery through (straight form) and retrieval of (corkscrew form) a stroke-causing thrombus (blood clot) in the brain. Thermal imaging of the microactuator during actuation in air indicated that the steady-state temperature rise caused by Joule heating varied quadratically with applied current and that actuation occurred near the glass transition temperature of the SMP (86 degrees C). To demonstrate clinical application, the device was used to retrieve a blood clot in a water-filled silicone neurovascular model. Numerical modeling of the heat transfer to the surrounding blood and associated thermal effects on the adjacent artery potentially encountered during clinical use suggested that any thermal damage would likely be confined to localized areas where the microactuator was touching the artery wall. This shape memory mechanical thrombectomy device is a promising tool for treating ischemic stroke without the need for infusion of clot-dissolving drugs.

  5. Hydrothermal fabrication of octahedral-shaped Fe3O4 nanoparticles and their magnetorheological response

    NASA Astrophysics Data System (ADS)

    Jung, H. S.; Choi, H. J.

    2015-05-01

    Octahedral-shaped Fe3O4 nanoparticles were synthesized in the presence of 1,3-diaminopropane using a hydrothermal method and assessed as a potential magnetorheological (MR) material. Their morphology, crystal structure, and magnetic properties were examined by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and vibrating sample magnetometry, respectively. The MR characteristics of the octahedral-shaped, Fe3O4 nanoparticle-based MR particles when dispersed in silicone oil with a 10 vol. % particle concentration were examined using a rotational rheometer under an external magnetic field. The resulting MR fluids exhibited a Bingham-like behavior with a distinctive yield stress from their flow curves.

  6. Fourcross shaped metamaterial filters fabricated from high temperature superconducting YBCO and Au thin films for terahertz waves

    NASA Astrophysics Data System (ADS)

    Demirhan, Y.; Alaboz, H.; Nebioğlu, M. A.; Mulla, B.; Akkaya, M.; Altan, H.; Sabah, C.; Ozyuzer, L.

    2017-07-01

    In this study, we present a new, unique fourcross shaped metamaterial terahertz (THz) filter fabricated from both gold thin films and YBa2Cu3O7-d high T c superconducting thin films. A commercial electromagnetic simulation software, CST Microwave Studio, is used to design and optimize the metamaterial filter structures. The proposed fourcross shaped rectangular filter structure consists of periodic metallic rings where strip lines are located at the sides of the ring. Fourcross metamaterial filters are fabricated by using e-beam lithography and ion beam etching techniques. Terahertz time-domain spectroscopy measurements validated the design predictions for both the center frequencies and bandwidths of the resonances due to the fourcross structures. The resonance switching of the transmission spectra was investigated by lowering the temperature below the critical transition temperature. This resonance switching effect is not observed in filters made up of metals. This novel fourcross rectangular resonator with a temperature-dependent resonance behavior holds great potential for active, tunable and low loss THz devices for imaging, sensing, and detection applications.

  7. Influence of cell shape on mechanical properties of Ti-6Al-4V meshes fabricated by electron beam melting method.

    PubMed

    Li, S J; Xu, Q S; Wang, Z; Hou, W T; Hao, Y L; Yang, R; Murr, L E

    2014-10-01

    Ti-6Al-4V reticulated meshes with different elements (cubic, G7 and rhombic dodecahedron) in Materialise software were fabricated by additive manufacturing using the electron beam melting (EBM) method, and the effects of cell shape on the mechanical properties of these samples were studied. The results showed that these cellular structures with porosities of 88-58% had compressive strength and elastic modulus in the range 10-300MPa and 0.5-15GPa, respectively. The compressive strength and deformation behavior of these meshes were determined by the coupling of the buckling and bending deformation of struts. Meshes that were dominated by buckling deformation showed relatively high collapse strength and were prone to exhibit brittle characteristics in their stress-strain curves. For meshes dominated by bending deformation, the elastic deformation corresponded well to the Gibson-Ashby model. By enhancing the effect of bending deformation, the stress-strain curve characteristics can change from brittle to ductile (the smooth plateau area). Therefore, Ti-6Al-4V cellular solids with high strength, low modulus and desirable deformation behavior could be fabricated through the cell shape design using the EBM technique. Copyright © 2014 Acta Materialia Inc. All rights reserved.

  8. Properties of Porous TiNbZr Shape Memory Alloy Fabricated by Mechanical Alloying and Hot Isostatic Pressing

    NASA Astrophysics Data System (ADS)

    Ma, L. W.; Chung, C. Y.; Tong, Y. X.; Zheng, Y. F.

    2011-07-01

    In the past decades, systematic researches have been focused on studying Ti-Nb-based SMAs by adding ternary elements, such as Mo, Sn, Zr, etc. However, only arc melting or induction melting methods, with subsequent hot or cold rolling, were used to fabricate these Ni-free SMAs. There is no work related to powder metallurgy and porous structures. This study focuses on the fabrication and characterization of porous Ti-22Nb-6Zr (at.%) shape memory alloys produced using elemental powders by means of mechanical alloying and hot isostatic pressing. It is found that the porous Ti-22Nb-6Zr alloys prepared by the HIP process exhibit a homogenous pore distribution with spherical pores, while the pores have irregular shape in the specimen prepared by conventional sintering. X-ray diffraction analysis showed that the solid solution-treated Ti-22Nb-6Zr alloy consists of both β phase and α″ martensite phase. Morphologies of martensite were observed. Finally, the porous Ti-22Nb-6Zr SMAs produced by both MA and HIP exhibit good mechanical properties, such as superior superelasticity, with maximum recoverable strain of ~3% and high compressive strength.

  9. A finger-shaped tactile sensor for fabric surfaces evaluation by 2-dimensional active sliding touch.

    PubMed

    Hu, Haihua; Han, Yezhen; Song, Aiguo; Chen, Shanguang; Wang, Chunhui; Wang, Zheng

    2014-03-11

    Sliding tactile perception is a basic function for human beings to determine the mechanical properties of object surfaces and recognize materials. Imitating this process, this paper proposes a novel finger-shaped tactile sensor based on a thin piezoelectric polyvinylidene fluoride (PVDF) film for surface texture measurement. A parallelogram mechanism is designed to ensure that the sensor applies a constant contact force perpendicular to the object surface, and a 2-dimensional movable mechanical structure is utilized to generate the relative motion at a certain speed between the sensor and the object surface. By controlling the 2-dimensional motion of the finger-shaped sensor along the object surface, small height/depth variation of surface texture changes the output charge of PVDF film then surface texture can be measured. In this paper, the finger-shaped tactile sensor is used to evaluate and classify five different kinds of linen. Fast Fourier Transformation (FFT) is utilized to get original attribute data of surface in the frequency domain, and principal component analysis (PCA) is used to compress the attribute data and extract feature information. Finally, low dimensional features are classified by Support Vector Machine (SVM). The experimental results show that this finger-shaped tactile sensor is effective and high accurate for discriminating the five textures.

  10. A Finger-Shaped Tactile Sensor for Fabric Surfaces Evaluation by 2-Dimensional Active Sliding Touch

    PubMed Central

    Hu, Haihua; Han, Yezhen; Song, Aiguo; Chen, Shanguang; Wang, Chunhui; Wang, Zheng

    2014-01-01

    Sliding tactile perception is a basic function for human beings to determine the mechanical properties of object surfaces and recognize materials. Imitating this process, this paper proposes a novel finger-shaped tactile sensor based on a thin piezoelectric polyvinylidene fluoride (PVDF) film for surface texture measurement. A parallelogram mechanism is designed to ensure that the sensor applies a constant contact force perpendicular to the object surface, and a 2-dimensional movable mechanical structure is utilized to generate the relative motion at a certain speed between the sensor and the object surface. By controlling the 2-dimensional motion of the finger-shaped sensor along the object surface, small height/depth variation of surface texture changes the output charge of PVDF film then surface texture can be measured. In this paper, the finger-shaped tactile sensor is used to evaluate and classify five different kinds of linen. Fast Fourier Transformation (FFT) is utilized to get original attribute data of surface in the frequency domain, and principal component analysis (PCA) is used to compress the attribute data and extract feature information. Finally, low dimensional features are classified by Support Vector Machine (SVM). The experimental results show that this finger-shaped tactile sensor is effective and high accurate for discriminating the five textures. PMID:24618775

  11. Basic properties of full-size st ructural flakeboards fabricated with flakes on a shaping lathe

    Treesearch

    Eddie W. Prie

    1977-01-01

    Structural exterior flakeboards manufactured in 4 by 8 ft (1.22 by 2.44 m ) size with phenolic resin and flakes produced on a shaping-lathe headrig were evaluated for plate shear modulus, internal bond, bending properties, and 24-hour water soak stability. Both mixed and single species flakeboards were produced. Panels with mixed flakes had 20% by weight of hickory,...

  12. A study of shape-dependent partial volume correction in pet imaging using ellipsoidal phantoms fabricated via rapid prototyping

    NASA Astrophysics Data System (ADS)

    Mille, Matthew M.

    Positron emission tomography (PET) with 2-[18F]fluoro-2-deoxy-D-glucose (FDG) is being increasingly recognized as an important tool for quantitative assessment of tumor response because of its ability to capture functional information about the tumor's metabolism. However, despite many advances in PET technology, measurements of tumor radiopharmaceutical uptake in PET are still challenged by issues of accuracy and consistency, thereby compromising the use of PET as a surrogate endpoint in clinical trials. One limiting component of the overall uncertainty in PET is the relatively poor spatial resolution of the images which directly affects the accuracy of the tumor radioactivity measurements. These spatial resolution effects, colloquially known as the partial volume effect (PVE), are a function of the characteristics of the scanner as well as the tumor being imaged. Previous efforts have shown that the PVE depends strongly on the tumor volume and the background-to-tumor activity concentration ratio. The PVE is also suspected to be a function of tumor shape, although to date no systematic study of this effect has been performed. This dissertation seeks to help fill the gap in the current knowledge about the shape-dependence of the PVE by attempting to quantify, through both theoretical calculation and experimental measurement, the magnitude of the shape effect for ellipsoidal tumors. An experimental investigation of the tumor shape effect necessarily requires tumor phantoms of multiple shapes. Hence, a prerequisite for this research was the design and fabrication of hollow tumor phantoms which could be filled uniformly with radioactivity and imaged on a PET scanner. The phantom fabrication was achieved with the aid of stereolithography and included prolate ellipsoids of various axis ratios. The primary experimental method involved filling the tumor phantoms with solutions of 18F whose activity concentrations were known and traceable to primary radioactivity standards

  13. Roll-to-roll hot embossing system with shape preserving mechanism for the large-area fabrication of microstructures

    NASA Astrophysics Data System (ADS)

    Peng, Linfa; Wu, Hao; Shu, Yunyi; Yi, Peiyun; Deng, Yujun; Lai, Xinmin

    2016-10-01

    Roll-to-roll (R2R) hot embossing is a promising approach to fulfilling the demands of high throughput fabrication of large-area polymeric components with micro-structure arrays which have been widely employed in the domains of optics, optoelectronics, biology, chemistry, etc. Nevertheless, the characteristic of continuous and fast forming for the R2R hot embossing process limits material flow during filling stage and results in significant springback during demolding stage. As a result, forming defects usually appear and the process window is very narrow which hinders the industrialization of this technology. This study developed a R2R hot embossing machine and proposed a shape preserving mechanism to extend the material filling time and realized the cooling effect during the demolding process. Comparative experiments were conducted on the R2R hot embossing process for micro-pyramid arrays to understand the effect of shape preserving mechanism. The influence of tension force and encapsulation angle to the forming quality was systematically analyzed. Furthermore, the influence of processing parameters has been investigated by using the one-variable-at-a-time method. Afterwards, a series of experiments based on the central composite design approach have been conducted for the analysis of variance and the establishment of empirical models of the R2R hot embossing process. As a result, the process window was extended by the shape preserving mechanism. More importantly, the feeding speed was improved from 0.5 m min-1 to 2.5 m min-1 for the large-area fabrication of micro-pyramid arrays, which is very attractive to the industrialization of this technology.

  14. Nanograined Net-Shaped Fabrication of Rhenium Components by EB-PVD

    SciTech Connect

    Singh, Jogender; Wolfe, Douglas E.

    2004-02-04

    Cost-effective net-shaped forming components have brought considerable interest into DoD, NASA and DoE. Electron beam physical vapor deposition (EB-PVD) offers flexibility in forming net-shaped components with tailored microstructure and chemistry. High purity rhenium (Re) components including rhenium-coated graphite balls, Re- plates and tubes have been successfully manufactured by EB-PVD. EB-PVD Re components exhibited sub-micron and nano-sized grains with high hardness and strength as compared to CVD. It is estimated that the cost of Re components manufactured by EB-PVD would be less than the current CVD and powder-HIP Technologies.

  15. Electron Beam Freeform Fabrication (EBF3) for Cost Effective Near-Net Shape Manufacturing

    NASA Technical Reports Server (NTRS)

    Taminger, Karen M.; Hafley, Robert A.

    2006-01-01

    Manufacturing of structural metal parts directly from computer aided design (CAD) data has been investigated by numerous researchers over the past decade. Researchers at NASA Langley Research Center are developing a new solid freeform fabrication process, electron beam freeform fabrication (EBF3), as a rapid metal deposition process that works efficiently with a variety of weldable alloys. EBF3 deposits of 2219 aluminium and Ti-6Al-4V have exhibited a range of grain morphologies depending upon the deposition parameters. These materials have exhibited excellent tensile properties comparable to typical handbook data for wrought plate product after post-processing heat treatments. The EBF3 process is capable of bulk metal deposition at deposition rates in excess of 2500 cubic centimeters per hour (150 in3/hr) or finer detail at lower deposition rates, depending upon the desired application. This process offers the potential for rapidly adding structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure. Selective addition of metal onto simpler blanks of material can have a significant effect on lead time reduction and lower material and machining costs.

  16. Electron Beam Freeform Fabrication for Cost Effective Near-Net Shape Manufacturing

    NASA Technical Reports Server (NTRS)

    Taminger, Karen M.; Hafley, Robert A.

    2006-01-01

    Manufacturing of structural metal parts directly from computer aided design (CAD) data has been investigated by numerous researchers over the past decade. Researchers at NASA Langley Research Center are developing a new solid freeform fabrication process, electron beam freeform fabrication (EBF3), as a rapid metal deposition process that works efficiently with a variety of weldable alloys. EBF3 deposits of 2219 aluminium and Ti-6Al-4V have exhibited a range of grain morphologies depending upon the deposition parameters. These materials have exhibited excellent tensile properties comparable to typical handbook data for wrought plate product after post-processing heat treatments. The EBF3 process is capable of bulk metal deposition at deposition rates in excess of 2500 cm3/hr (150 in3/hr) or finer detail at lower deposition rates, depending upon the desired application. This process offers the potential for rapidly adding structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure. Selective addition of metal onto simpler blanks of material can have a significant effect on lead time reduction and lower material and machining costs.

  17. Metal Injection Moulding: A Near Net Shape Fabrication Method for the Manufacture of Turbine Engine Component

    DTIC Science & Technology

    2006-05-01

    annealing. 1 INTRODUCTION Nickel superalloys such as Inconel 625 were developed to withstand the intense conditions present in gas turbine engines...where carbides present. Acicular (delta) Blocky irregular (Laves) 866°C-1033°C (1100°F-1400°F) γ’’ Plate of disc shaped particles...1991), The Influence of Processing Variables on the Microstructure and Properties of PM 625 Alloy, Superalloys 718, 625, 706 and Various Derivatives

  18. Replication molds having nanometer-scale shape control fabricated by means of oxidation and etching.

    PubMed

    Kim, G M; Kovalgin, A; Holleman, J; Brugger, J

    2002-02-01

    A means of accurate control of the curvature radius of molds that are used in nanostructure replication techniques is presented. The local non-uniform growth of SiO2 at regions with high curvature is used to fabricate molds with a curvature radius ranging anywhere between 10 and 250 nm. The mold radius is predicted by numerical simulation as a function of oxidation temperature and time and confirmed by a series of oxidation and etching experiments. The silicon, silicon dioxide, and polymer nanostructures are analyzed by scanning electron microscopy and compared with the theory. Replication into photo-plastic polymer from various sharp and round molds is performed, and their properties are discussed. Our results are useful for designing nanostructures in the area of soft lithography and nanoprobe engineering.

  19. Fabrication of anatomically-shaped cartilage constructs using decellularized cartilage-derived matrix scaffolds.

    PubMed

    Rowland, Christopher R; Colucci, Lina A; Guilak, Farshid

    2016-06-01

    The native extracellular matrix of cartilage contains entrapped growth factors as well as tissue-specific epitopes for cell-matrix interactions, which make it a potentially attractive biomaterial for cartilage tissue engineering. A limitation to this approach is that the native cartilage extracellular matrix possesses a pore size of only a few nanometers, which inhibits cellular infiltration. Efforts to increase the pore size of cartilage-derived matrix (CDM) scaffolds dramatically attenuate their mechanical properties, which makes them susceptible to cell-mediated contraction. In previous studies, we have demonstrated that collagen crosslinking techniques are capable of preventing cell-mediated contraction in CDM disks. In the current study, we investigated the effects of CDM concentration and pore architecture on the ability of CDM scaffolds to resist cell-mediated contraction. Increasing CDM concentration significantly increased scaffold mechanical properties, which played an important role in preventing contraction, and only the highest CDM concentration (11% w/w) was able to retain the original scaffold dimensions. However, the increase in CDM concentration led to a concomitant decrease in porosity and pore size. Generating a temperature gradient during the freezing process resulted in unidirectional freezing, which aligned the formation of ice crystals during the freezing process and in turn produced aligned pores in CDM scaffolds. These aligned pores increased the pore size of CDM scaffolds at all CDM concentrations, and greatly facilitated infiltration by mesenchymal stem cells (MSCs). These methods were used to fabricate of anatomically-relevant CDM hemispheres. CDM hemispheres with aligned pores supported uniform MSC infiltration and matrix deposition. Furthermore, these CDM hemispheres retained their original architecture and did not contract, warp, curl, or splay throughout the entire 28-day culture period. These findings demonstrate that given the

  20. Top-Down Particle Fabrication: Control of Size and Shape for Diagnostic Imaging and Drug Delivery

    PubMed Central

    Canelas, Dorian A.; Herlihy, Kevin P.; DeSimone, Joseph M.

    2009-01-01

    This review discusses rational design of particles for use as therapeutic vectors and diagnostic imaging agent carriers. The emerging importance of both particle size and shape is considered, and the adaptation and modification of soft lithography methods to produce nanoparticles is highlighted. To this end, studies utilizing particles made via a process called Particle Replication In Non-wetting Templates (PRINT™) are discussed. In addition, insights gained into therapeutic cargo and imaging agent delivery from related types of polymer-based carriers are considered. PMID:20049805

  1. Texture and Crystal Orientation in Ti-6Al-4V Builds Fabricated by Shaped Metal Deposition

    NASA Astrophysics Data System (ADS)

    Baufeld, Bernd; van der Biest, Omer; Dillien, Steven

    2010-08-01

    The texture and crystal orientation of Ti-6Al-4V components, manufactured by shaped metal deposition (SMD), is investigated. SMD is a novel rapid prototyping tungsten inert gas (TIG) welding technique leading to near-net-shape components. This involves sequential layer by layer deposition with repeated partial melting and heat treatment, which results in epitaxial growth of large elongated prior β grains. This leads to a directionally solidified texture, where the prior β grains exhibit only a small misorientation with each other. The β grains grow in left< { 100} rightrangle direction with a second left< { 100} rightrangle direction perpendicular to the wall surface. During cooling, the α phase transformation follows the Burgers orientation relationship leading to a Widmanstätten structure, with orientation relations between most of the α lamellae and also of the residual β phase. The directionally solidification and the transformation into the α phase following the Burgers relationship results in a texture, where the hcp pole figures look similar to bcc pole figures.

  2. Research on a Nonwoven Fabric Made from Multi-Block Biodegradable Copolymer Based on l-Lactide, Glycolide, and Trimethylene Carbonate with Shape Memory.

    PubMed

    Walczak, Joanna; Chrzanowski, Michał; Krucińska, Izabella

    2017-08-10

    The presented paper concerns scientific research on processing a poly(lactide-co-glycolide-co-trimethylene carbonate) copolymer (PLLAGLTMC) with thermally induced shape memory and a transition temperature around human body temperature. The material in the literature called terpolymer was used to produce smart, nonwoven fabric with the melt blowing technique. Bioresorbable and biocompatible terpolymers with shape memory have been investigated for its medical applications, such as cardiovascular stents. There are several research studies on shape memory in polymers, but this phenomenon has not been widely studied in textile products made from shape memory polymers (SMPs). The current research aims to explore the characteristics of the PLLAGLTMC nonwoven fabric in detail and the mechanism of its shape memory behavior. In this study, the nonwoven fabric was subjected to thermo-mechanical, morphological, and shape memory analysis. The thermo-mechanical and structural properties were investigated by means of differential scanning calorimetry, dynamic mechanical analysis, scanning electron microscopic examination, and mercury porosimetry measurements. Eventually, the gathered results confirmed that the nonwoven fabric possessed characteristics that classified it as a smart material with potential applications in medicine.

  3. Highly stretchable and shape-controllable three-dimensional antenna fabricated by "Cut-Transfer-Release" method.

    PubMed

    Yan, Zhuocheng; Pan, Taisong; Yao, Guang; Liao, Feiyi; Huang, Zhenlong; Zhang, Hulin; Gao, Min; Zhang, Yin; Lin, Yuan

    2017-02-13

    Recent progresses on the Kirigami-inspired method provide a new idea to assemble three-dimensional (3D) functional structures with conventional materials by releasing the prestrained elastomeric substrates. In this paper, highly stretchable serpentine-like antenna is fabricated by a simple and quick "Cut-Transfer-Release" method for assembling stretchable 3D functional structures on an elastomeric substrate with a controlled shape. The mechanical reliability of the serpentine-like 3D stretchable antenna is evaluated by the finite element method and experiments. The antenna shows consistent radio frequency performance with center frequency at 5.6 GHz during stretching up to 200%. The 3D structure is also able to eliminate the hand effect observed commonly in the conventional antenna. This work is expected to spur the applications of novel 3D structures in the stretchable electronics.

  4. Highly stretchable and shape-controllable three-dimensional antenna fabricated by “Cut-Transfer-Release” method

    PubMed Central

    Yan, Zhuocheng; Pan, Taisong; Yao, Guang; Liao, Feiyi; Huang, Zhenlong; Zhang, Hulin; Gao, Min; Zhang, Yin; Lin, Yuan

    2017-01-01

    Recent progresses on the Kirigami-inspired method provide a new idea to assemble three-dimensional (3D) functional structures with conventional materials by releasing the prestrained elastomeric substrates. In this paper, highly stretchable serpentine-like antenna is fabricated by a simple and quick “Cut-Transfer-Release” method for assembling stretchable 3D functional structures on an elastomeric substrate with a controlled shape. The mechanical reliability of the serpentine-like 3D stretchable antenna is evaluated by the finite element method and experiments. The antenna shows consistent radio frequency performance with center frequency at 5.6 GHz during stretching up to 200%. The 3D structure is also able to eliminate the hand effect observed commonly in the conventional antenna. This work is expected to spur the applications of novel 3D structures in the stretchable electronics. PMID:28198812

  5. Highly stretchable and shape-controllable three-dimensional antenna fabricated by “Cut-Transfer-Release” method

    NASA Astrophysics Data System (ADS)

    Yan, Zhuocheng; Pan, Taisong; Yao, Guang; Liao, Feiyi; Huang, Zhenlong; Zhang, Hulin; Gao, Min; Zhang, Yin; Lin, Yuan

    2017-02-01

    Recent progresses on the Kirigami-inspired method provide a new idea to assemble three-dimensional (3D) functional structures with conventional materials by releasing the prestrained elastomeric substrates. In this paper, highly stretchable serpentine-like antenna is fabricated by a simple and quick “Cut-Transfer-Release” method for assembling stretchable 3D functional structures on an elastomeric substrate with a controlled shape. The mechanical reliability of the serpentine-like 3D stretchable antenna is evaluated by the finite element method and experiments. The antenna shows consistent radio frequency performance with center frequency at 5.6 GHz during stretching up to 200%. The 3D structure is also able to eliminate the hand effect observed commonly in the conventional antenna. This work is expected to spur the applications of novel 3D structures in the stretchable electronics.

  6. General logarithmic image processing convolution.

    PubMed

    Palomares, Jose M; González, Jesús; Ros, Eduardo; Prieto, Alberto

    2006-11-01

    The logarithmic image processing model (LIP) is a robust mathematical framework, which, among other benefits, behaves invariantly to illumination changes. This paper presents, for the first time, two general formulations of the 2-D convolution of separable kernels under the LIP paradigm. Although both formulations are mathematically equivalent, one of them has been designed avoiding the operations which are computationally expensive in current computers. Therefore, this fast LIP convolution method allows to obtain significant speedups and is more adequate for real-time processing. In order to support these statements, some experimental results are shown in Section V.

  7. Design of convolutional tornado code

    NASA Astrophysics Data System (ADS)

    Zhou, Hui; Yang, Yao; Gao, Hongmin; Tan, Lu

    2017-09-01

    As a linear block code, the traditional tornado (tTN) code is inefficient in burst-erasure environment and its multi-level structure may lead to high encoding/decoding complexity. This paper presents a convolutional tornado (cTN) code which is able to improve the burst-erasure protection capability by applying the convolution property to the tTN code, and reduce computational complexity by abrogating the multi-level structure. The simulation results show that cTN code can provide a better packet loss protection performance with lower computation complexity than tTN code.

  8. Net Shaped Component Fabrication of Refractory Metal Alloys using Vacuum Plasma Spraying

    NASA Technical Reports Server (NTRS)

    Sen, S.; ODell, S.; Gorti, S.; Litchford, R.

    2006-01-01

    The vacuum plasma spraying (VPS) technique was employed to produce dense and net shaped components of a new tungsten-rhenium (W-Re) refractory metal alloy. The fine grain size obtained using this technique enhanced the mechanical properties of the alloy at elevated temperatures. The alloy development also included incorporation of thermodynamically stable dispersion phases to pin down grain boundaries at elevated temperatures and thereby circumventing the inherent problem of recrystallization of refractory alloys at elevated temperatures. Requirements for such alloys as related to high temperature space propulsion components will be discussed. Grain size distribution as a function of cooling rate and dispersion phase loading will be presented. Mechanical testing and grain growth results as a function of temperature will also be discussed.

  9. Net Shaped Component Fabrication of Refractory Metal Alloys using Vacuum Plasma Spraying

    NASA Technical Reports Server (NTRS)

    Sen, S.; ODell, S.; Gorti, S.; Litchford, R.

    2006-01-01

    The vacuum plasma spraying (VPS) technique was employed to produce dense and net shaped components of a new tungsten-rhenium (W-Re) refractory metal alloy. The fine grain size obtained using this technique enhanced the mechanical properties of the alloy at elevated temperatures. The alloy development also included incorporation of thermodynamically stable dispersion phases to pin down grain boundaries at elevated temperatures and thereby circumventing the inherent problem of recrystallization of refractory alloys at elevated temperatures. Requirements for such alloys as related to high temperature space propulsion components will be discussed. Grain size distribution as a function of cooling rate and dispersion phase loading will be presented. Mechanical testing and grain growth results as a function of temperature will also be discussed.

  10. Facile fabrication of plate-shaped hydrohausmannite as electrode material for supercapacitors

    NASA Astrophysics Data System (ADS)

    Liang, Jun; Chai, Yao; Li, Deli; Li, Meng; Lu, Jiaxue; Li, Li; Luo, Min

    2017-08-01

    A simple and one-step solvothermal synthesis method has been developed to prepare two-dimensional (2-D) hydrohausmannite ((Mn4-2xMnx)Mn8O16-x(OH)x) nanoplates with radial length of 300 nm and thickness of about 25 nm in a binary ethanediamine/water solvent system. The formation mechanism of hydrohausmannite is suggested. As an anode material for electrochemical capacitors, the plate-shaped hydrohausmannite not only displays a high specific capacity (215 at 0.1 A g-1) and good rate capability, but also shows good stable performance along with 94% specific capacity retained after 3000 cycle tests. The method can be easily controlled and expected to be applicable for the large-scale preparation of the 2-D hydrohausmannite.

  11. Improved cost-effective fabrication of arbitrarily shaped μIPMC transducers

    NASA Astrophysics Data System (ADS)

    Feng, Guo-Hua; Chen, Ri-Hong

    2008-01-01

    Conventional ionic polymer-metal composite (IPMC) production cuts individual transducers from bulk IPMC sheets. This paper presents a novel photolithographic technique that grows a large array of identical devices on a thin (~µm range) parylene diaphragm supported on a perforated substrate of material that is immune to the subsequent processing liquids. In particular, the new technique relies on a unique wax fill-up and removal concept that can produce arbitrarily shaped Nafion films with micron feature size. The developed process is cheap and results in devices of high uniformity and reliability, with greater design flexibility. Microtensile testing characterizes the fracture profiles of the non-electroded Nafion film and IPMC. Young's modulus is characterized, as well as maximum displacement and current consumption under various loading, driving voltages, waveforms and frequencies. High product quality and low process costs make this process of interest for mass production of micromachined IPMC transducers.

  12. Convolutional virtual electric field for image segmentation using active contours.

    PubMed

    Wang, Yuanquan; Zhu, Ce; Zhang, Jiawan; Jian, Yuden

    2014-01-01

    Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load. The virtual electric field (VEF) model, which can be implemented in real time using fast Fourier transform (FFT), has been proposed later as a remedy for the GVF model. In this work, we present an extension of the VEF model, which is referred to as CONvolutional Virtual Electric Field, CONVEF for short. This proposed CONVEF model takes the VEF model as a convolution operation and employs a modified distance in the convolution kernel. The CONVEF model is also closely related to the vector field convolution (VFC) model. Compared with the GVF, VEF and VFC models, the CONVEF model possesses not only some desirable properties of these models, such as enlarged capture range, u-shape concavity convergence, subject contour convergence and initialization insensitivity, but also some other interesting properties such as G-shape concavity convergence, neighboring objects separation, and noise suppression and simultaneously weak edge preserving. Meanwhile, the CONVEF model can also be implemented in real-time by using FFT. Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images.

  13. Design and Fabrication of a Biodegradable, Covalently Crosslinked Shape-Memory Alginate Scaffold for Cell and Growth Factor Delivery

    PubMed Central

    Wang, Lin; Shansky, Janet; Borselli, Cristina; Mooney, David

    2012-01-01

    The successful use of transplanted cells and/or growth factors for tissue repair is limited by a significant cell loss and/or rapid growth factor diffusion soon after implantation. Highly porous alginate scaffolds formed with covalent crosslinking have been used to improve cell survival and growth factor release kinetics, but require open-wound surgical procedures for insertion and have not previously been designed to readily degrade in vivo. In this study, a biodegradable, partially crosslinked alginate scaffold with shape-memory properties was fabricated for minimally invasive surgical applications. A mixture of high and low molecular weight partially oxidized alginate modified with RGD peptides was covalently crosslinked using carbodiimide chemistry. The scaffold was compressible 11-fold and returned to its original shape when rehydrated. Scaffold degradation properties in vitro indicated ∼85% mass loss by 28 days. The greater than 90% porous scaffolds released the recombinant growth factor insulin-like growth factor-1 over several days in vitro and allowed skeletal muscle cell survival, proliferation, and migration from the scaffold over a 28-day period. The compressible scaffold thus has the potential to be delivered by a minimally invasive technique, and when rehydrated in vivo with cells and/or growth factors, could serve as a temporary delivery vehicle for tissue repair. PMID:22646518

  14. Design and fabrication of a bat-inspired flapping-flight platform using shape memory alloy muscles and joints

    NASA Astrophysics Data System (ADS)

    Furst, Stephen J.; Bunget, George; Seelecke, Stefan

    2013-01-01

    This work focuses on the development of a concept for a micro-air vehicle (MAV) based on a bio-inspired flapping motion that is generated from integrated smart materials. Since many smart materials have their own biomimetic characteristics and the potential to be highly efficient, lightweight, and streamlined, they are ideal candidates for use in structural or actuator components in MAVs. In this work, shape memory alloy (SMA) actuator wires are used as analogs for biological muscles, and super-elastic SMAs are implemented as flexible joints capable of large bending angles. While biological organisms have an intrinsic sensing array composed of nerves, the SMA wires also provide self-sensing by virtue of a phase-dependent resistance change. Study of the biology and flight characteristics of natural fliers concluded that the bat provides an ideal platform for SMA muscle wires because of its comparatively low wingbeat frequency and superb maneuverability. A first-generation prototype is built to further the understanding of fabricating Nature’s designs. The engineering design is then improved further in a second-generation prototype that combines 3D printing and new techniques for embedding SMA wires and shaping SMA joints for improved robustness, reproducibility, and lifetime. These prototypes are on display at the North Carolina Museum of Natural Science’s Nature Research Center, which has the goal of bridging the gaps between biology and engineering.

  15. Investigation on the corner effect of L-shaped tunneling field-effect transistors and their fabrication method.

    PubMed

    Kim, Sang Wan; Choi, Woo Young; Sun, Min-Chul; Park, Byung-Gook

    2013-09-01

    In this work, electrical characteristics of L-shaped tunneling field-effect transistors (TFETs) have been studied and optimized by a commercial device simulator: Synopsys Sentaurus. Unlike our previous study performed by using Silvaco Atlas, there exists a kink phenomenon in a transfer curve which degrades the subthreshold swing (SS) and on-current (lon) of TFETs. According to simulation results, the kink results from abrupt source doping. Rounding the source junction edge with gradual doping profile is helpful to alleviate it. Based on those results, a novel fabrication flow has been proposed to suppress the kink effect induced by source corners. It is predicted that the performance of L-shaped TFETs is improved in terms of SS and Ion under the optimized process condition. Furthremore, the effect of high-k gate dielectric and narrow band gap material on device performance has been examined. Using 2-nm-thick HfO2 for gate dielectric and Si0.7Ge0.3 for intrinsic tunneling region, gate controllability to the channel and tunneling probability have been enhanced. As a result, its threshold voltage (Vth), SS and Ion have been improved by 0.13 V, 16 mV/dec, and 3.62 microA/microm, respectively.

  16. Easy and cheap fabrication of ordered pyramidal-shaped plasmonic substrates for detection and quantitative analysis using surface-enhanced Raman spectroscopy.

    PubMed

    Leordean, Cosmin; Gabudean, Ana-Maria; Canpean, Valentin; Astilean, Simion

    2013-09-07

    In this work we present a simple approach for the fabrication of periodically ordered pyramidal-shaped metallic nanostructures and demonstrate their efficiency as SERS active substrates. Our method for the fabrication of the plasmonic substrate is based on nanoimprint lithography and exploits the thermal properties of two classes of polymers, thermoplastics and hydrogels. During the heating process the thermoplastic polymers will start to melt whereas the hydrogel polymers will form a solid due to the evaporation of water molecules adsorbed during the dissolving process. Using this approach we fabricate highly ordered pyramidal-shaped nanostructures using the texture of a commercial DVD as the initial mold. This technique represents a low-cost alternative to the classical lithography techniques, allowing the fabrication over large areas (~cm(2)) of periodically ordered nanostructures in a controlled and reproducible manner. The SERS efficiency of the fabricated substrate is demonstrated through the detection of urea molecules found in the fingerprint. In addition, due to the periodicity of the pyramidal-shaped structures, the fabricated substrate can be successfully employed to correlate the intensity of the specific SERS peak of urea with the molecules concentration, offering thus the possibility of developing a quantitative SERS renal sensor.

  17. Shape-controlled fabrication of magnetite silver hybrid nanoparticles with high performance magnetic hyperthermia.

    PubMed

    Ding, Qi; Liu, Dongfang; Guo, Dawei; Yang, Fang; Pang, Xingyun; Che, Renchao; Zhou, Naizhen; Xie, Jun; Sun, Jianfei; Huang, Zhihai; Gu, Ning

    2017-04-01

    Superparamagnetic Fe3O4 nanoparticles (NPs)-based hyperthermia is a promising non-invasive approach for cancer therapy. However, the heat transfer efficiency of Fe3O4 NPs is relative low, which hinders their practical clinical applications. Therefore, it is promising to improve the magnetic hyperthermia efficiency by exploring the higher performance magnetic NPs-based hybrid nanostructures. In the current study, it presents a straightforward in situ reduction method for the shape-controlled preparation of magnetite (Fe3O4) silver (Ag) hybrid NPs designed as magnetic hyperthermia heat mediators. The magnetite silver hybrid NPs with core-shell (Fe3O4@Ag) or heteromer (Fe3O4-Ag) structures exhibited a higher biocompatibility with SMMC-7721 cells and L02 cells than the individual Ag NPs. Importantly, in the magnetic hyperthermia, with the exposure to alternating current magnetic field, the Fe3O4@Ag and Fe3O4-Ag hybrid NPs indicated much better tumor suppression effect against SMMC-7721 cells than the individual Fe3O4 NPs in vitro and in vivo. These results demonstrate that the hybridisation of Fe3O4 and Ag NPs could greatly enhance the magnetic hyperthermia efficiency of Fe3O4 NPs. Therefore, the Fe3O4@Ag and Fe3O4-Ag hybrid NPs can be used to be as high performance magnetic hyperthermia mediators based on a simple and effective preparation approach.

  18. Inhibitor Discovery by Convolution ABPP.

    PubMed

    Chandrasekar, Balakumaran; Hong, Tram Ngoc; van der Hoorn, Renier A L

    2017-01-01

    Activity-based protein profiling (ABPP) has emerged as a powerful proteomic approach to study the active proteins in their native environment by using chemical probes that label active site residues in proteins. Traditionally, ABPP is classified as either comparative or competitive ABPP. In this protocol, we describe a simple method called convolution ABPP, which takes benefit from both the competitive and comparative ABPP. Convolution ABPP allows one to detect if a reduced signal observed during comparative ABPP could be due to the presence of inhibitors. In convolution ABPP, the proteomes are analyzed by comparing labeling intensities in two mixed proteomes that were labeled either before or after mixing. A reduction of labeling in the mix-and-label sample when compared to the label-and-mix sample indicates the presence of an inhibitor excess in one of the proteomes. This method is broadly applicable to detect inhibitors in proteomes against any proteome containing protein activities of interest. As a proof of concept, we applied convolution ABPP to analyze secreted proteomes from Pseudomonas syringae-infected Nicotiana benthamiana leaves to display the presence of a beta-galactosidase inhibitor.

  19. Convolutional neural network for pottery retrieval

    NASA Astrophysics Data System (ADS)

    Benhabiles, Halim; Tabia, Hedi

    2017-01-01

    The effectiveness of the convolutional neural network (CNN) has already been demonstrated in many challenging tasks of computer vision, such as image retrieval, action recognition, and object classification. This paper specifically exploits CNN to design local descriptors for content-based retrieval of complete or nearly complete three-dimensional (3-D) vessel replicas. Based on vector quantization, the designed descriptors are clustered to form a shape vocabulary. Then, each 3-D object is associated to a set of clusters (words) in that vocabulary. Finally, a weighted vector counting the occurrences of every word is computed. The reported experimental results on the 3-D pottery benchmark show the superior performance of the proposed method.

  20. Cost-Benefit Analysis for the Advanced Near Net Shape Technology (ANNST) Method for Fabricating Stiffened Cylinders

    NASA Technical Reports Server (NTRS)

    Stoner, Mary Cecilia; Hehir, Austin R.; Ivanco, Marie L.; Domack, Marcia S.

    2016-01-01

    This cost-benefit analysis assesses the benefits of the Advanced Near Net Shape Technology (ANNST) manufacturing process for fabricating integrally stiffened cylinders. These preliminary, rough order-of-magnitude results report a 46 to 58 percent reduction in production costs and a 7-percent reduction in weight over the conventional metallic manufacturing technique used in this study for comparison. Production cost savings of 35 to 58 percent were reported over the composite manufacturing technique used in this study for comparison; however, the ANNST concept was heavier. In this study, the predicted return on investment of equipment required for the ANNST method was ten cryogenic tank barrels when compared with conventional metallic manufacturing. The ANNST method was compared with the conventional multi-piece metallic construction and composite processes for fabricating integrally stiffened cylinders. A case study compared these three alternatives for manufacturing a cylinder of specified geometry, with particular focus placed on production costs and process complexity, with cost analyses performed by the analogy and parametric methods. Furthermore, a scalability study was conducted for three tank diameters to assess the highest potential payoff of the ANNST process for manufacture of large-diameter cryogenic tanks. The analytical hierarchy process (AHP) was subsequently used with a group of selected subject matter experts to assess the value of the various benefits achieved by the ANNST method for potential stakeholders. The AHP study results revealed that decreased final cylinder mass and quality assurance were the most valued benefits of cylinder manufacturing methods, therefore emphasizing the relevance of the benefits achieved with the ANNST process for future projects.

  1. Fabrication of cyclodextrins-procainamide supramolecular self-assembly: shape-shifting of nanosheet into microtubular structure.

    PubMed

    Siva, S; Kothai Nayaki, S; Rajendiran, N

    2015-05-20

    Encapsulation behavior of α- and β-cyclodextrins (α-CD, β-CD) with procainamide hydrochloride (PCA) has been investigated by absorption, fluorescence, time-resolved fluorescence, proton nuclear magnetic resonance spectroscopy, scanning electron microscope, Fourier transform-infrared spectroscopy, differential scanning calorimetry, and powder X-ray diffraction techniques. Spectral results revealed that PCA forms 1:2 drug-CD2 inclusion complexes with CDs. Novel supramolecular self-assemblies have been fabricated by inclusion complexation of PCA with α-CD/β-CD and characterized by transmission electron microscope and micro-Raman imaging. The obtained results from transmission electron microscope indicated that PCA/α-CD complex could form nano-sized particles. However, when the macrocyclic ring with six glucose units was switched into seven glucose units, the resultant PCA/β-CD complex could be self-assembled to micro-sized tubular structures. Shape-shifting of 2D nanosheet into 1D microtube by simple rolling mechanism was analyzed. Thermodynamic parameters of inclusion process were determined by Parameter Method 3 calculations.

  2. Miniaturized Band Stop FSS Using Convoluted Swastika Structure

    NASA Astrophysics Data System (ADS)

    Bilvam, Sridhar; Sivasamy, Ramprabhu; Kanagasabai, Malathi; Alsath M, Gulam Nabi; Baisakhiya, Sanjay

    2017-01-01

    This paper presents a miniaturized frequency selective surface (FSS) with stop band characteristics at the resonant frequency of 5.12 GHz. The unit cell size of the proposed FSS design is in the order of 0.095 λ×0.095 λ. The proposed unit cell is obtained by convoluting the arms of the basic swastika structure. The design provides fractional bandwidth of 9.0 % at the center frequency of 5.12 GHz in the 20 dB reference level of insertion loss. The symmetrical aspect of the design delivers identical response for both transverse electric (TE) and transverse magnetic (TM) modes thereby exhibiting polarization independent operation. The miniaturized design provides good angular independency for various incident angles. The dispersion analysis is done to substantiate the band stop operation of the convoluted swastika FSS. The proposed FSS is fabricated and its working is validated through measurements.

  3. Cantilever tilt causing amplitude related convolution in dynamic mode atomic force microscopy.

    PubMed

    Wang, Chunmei; Sun, Jielin; Itoh, Hiroshi; Shen, Dianhong; Hu, Jun

    2011-01-01

    It is well known that the topography in atomic force microscopy (AFM) is a convolution of the tip's shape and the sample's geometry. The classical convolution model was established in contact mode assuming a static probe, but it is no longer valid in dynamic mode AFM. It is still not well understood whether or how the vibration of the probe in dynamic mode affects the convolution. Such ignorance complicates the interpretation of the topography. Here we propose a convolution model for dynamic mode by taking into account the typical design of the cantilever tilt in AFMs, which leads to a different convolution from that in contact mode. Our model indicates that the cantilever tilt results in a dynamic convolution affected by the absolute value of the amplitude, especially in the case that corresponding contact convolution has sharp edges beyond certain angle. The effect was experimentally demonstrated by a perpendicular SiO(2)/Si super-lattice structure. Our model is useful for quantitative characterizations in dynamic mode, especially in probe characterization and critical dimension measurements.

  4. Cost-Benefit Analysis for the Advanced Near Net Shape Technology (ANNST) Method for Fabricating Stiffened Cylinders

    NASA Technical Reports Server (NTRS)

    Ivanco, Marie L.; Domack, Marcia S.; Stoner, Mary Cecilia; Hehir, Austin R.

    2016-01-01

    Low Technology Readiness Levels (TRLs) and high levels of uncertainty make it challenging to develop cost estimates of new technologies in the R&D phase. It is however essential for NASA to understand the costs and benefits associated with novel concepts, in order to prioritize research investments and evaluate the potential for technology transfer and commercialization. This paper proposes a framework to perform a cost-benefit analysis of a technology in the R&D phase. This framework was developed and used to assess the Advanced Near Net Shape Technology (ANNST) manufacturing process for fabricating integrally stiffened cylinders. The ANNST method was compared with the conventional multi-piece metallic construction and composite processes for fabricating integrally stiffened cylinders. Following the definition of a case study for a cryogenic tank cylinder of specified geometry, data was gathered through interviews with Subject Matter Experts (SMEs), with particular focus placed on production costs and process complexity. This data served as the basis to produce process flowcharts and timelines, mass estimates, and rough order-of-magnitude cost and schedule estimates. The scalability of the results was subsequently investigated to understand the variability of the results based on tank size. Lastly, once costs and benefits were identified, the Analytic Hierarchy Process (AHP) was used to assess the relative value of these achieved benefits for potential stakeholders. These preliminary, rough order-of-magnitude results predict a 46 to 58 percent reduction in production costs and a 7-percent reduction in weight over the conventional metallic manufacturing technique used in this study for comparison. Compared to the composite manufacturing technique, these results predict cost savings of 35 to 58 percent; however, the ANNST concept was heavier. In this study, the predicted return on investment of equipment required for the ANNST method was ten cryogenic tank barrels

  5. The Convolution Method in Neutrino Physics Searches

    SciTech Connect

    Tsakstara, V.; Kosmas, T. S.; Chasioti, V. C.; Divari, P. C.; Sinatkas, J.

    2007-12-26

    We concentrate on the convolution method used in nuclear and astro-nuclear physics studies and, in particular, in the investigation of the nuclear response of various neutrino detection targets to the energy-spectra of specific neutrino sources. Since the reaction cross sections of the neutrinos with nuclear detectors employed in experiments are extremely small, very fine and fast convolution techniques are required. Furthermore, sophisticated de-convolution methods are also needed whenever a comparison between calculated unfolded cross sections and existing convoluted results is necessary.

  6. On the growth and form of cortical convolutions

    NASA Astrophysics Data System (ADS)

    Tallinen, Tuomas; Chung, Jun Young; Rousseau, François; Girard, Nadine; Lefèvre, Julien; Mahadevan, L.

    2016-06-01

    The rapid growth of the human cortex during development is accompanied by the folding of the brain into a highly convoluted structure. Recent studies have focused on the genetic and cellular regulation of cortical growth, but understanding the formation of the gyral and sulcal convolutions also requires consideration of the geometry and physical shaping of the growing brain. To study this, we use magnetic resonance images to build a 3D-printed layered gel mimic of the developing smooth fetal brain; when immersed in a solvent, the outer layer swells relative to the core, mimicking cortical growth. This relative growth puts the outer layer into mechanical compression and leads to sulci and gyri similar to those in fetal brains. Starting with the same initial geometry, we also build numerical simulations of the brain modelled as a soft tissue with a growing cortex, and show that this also produces the characteristic patterns of convolutions over a realistic developmental course. All together, our results show that although many molecular determinants control the tangential expansion of the cortex, the size, shape, placement and orientation of the folds arise through iterations and variations of an elementary mechanical instability modulated by early fetal brain geometry.

  7. Radiative and convective properties of 316L Stainless Steel fabricated using the Laser Engineered Net Shaping process

    NASA Astrophysics Data System (ADS)

    Knopp, Jonathan

    Temperature evolution of metallic materials during the additive manufacturing process has direct influence in determining the materials microstructure and resultant characteristics. Through the power of Infrared (IR) thermography it is now possible to monitor thermal trends in a build structure, giving the power to adjust building parameters in real time. The IR camera views radiation in the IR wavelengths and determines temperature of an object by the amount of radiation emitted from the object in those wavelengths. Determining the amount of radiation emitted from the material, known as a materials emissivity, can be difficult in that emissivity is affected by both temperature and surface finish. It has been shown that the use of a micro-blackbody cavity can be used as an accurate reference temperature when the sample is held at thermal equilibrium. A micro-blackbody cavity was created in a sample of 316L Stainless Steel after being fabricated during using the Laser Engineered Net Shaping (LENS) process. Holding the sample at thermal equilibrium and using the micro-blackbody cavity as a reference and thermocouple as a second reference emissivity values were able to be obtained. IR thermography was also used to observe the manufacturing of these samples. When observing the IR thermography, patterns in the thermal history of the build were shown to be present as well as distinct cooling rates of the material. This information can be used to find true temperatures of 316L Stainless Steel during the LENS process for better control of desired material properties as well as future work in determining complete energy balance.

  8. Design and fabrication of 3D-printed anatomically shaped lumbar cage for intervertebral disc (IVD) degeneration treatment.

    PubMed

    Serra, T; Capelli, C; Toumpaniari, R; Orriss, I R; Leong, J J H; Dalgarno, K; Kalaskar, D M

    2016-07-19

    Spinal fusion is the gold standard surgical procedure for degenerative spinal conditions when conservative therapies have been unsuccessful in rehabilitation of patients. Novel strategies are required to improve biocompatibility and osseointegration of traditionally used materials for lumbar cages. Furthermore, new design and technologies are needed to bridge the gap due to the shortage of optimal implant sizes to fill the intervertebral disc defect. Within this context, additive manufacturing technology presents an excellent opportunity to fabricate ergonomic shape medical implants. The goal of this study is to design and manufacture a 3D-printed lumbar cage for lumbar interbody fusion. Optimisations of the proposed implant design and its printing parameters were achieved via in silico analysis. The final construct was characterised via scanning electron microscopy, contact angle, x-ray micro computed tomography (μCT), atomic force microscopy, and compressive test. Preliminary in vitro cell culture tests such as morphological assessment and metabolic activities were performed to access biocompatibility of 3D-printed constructs. Results of in silico analysis provided a useful platform to test preliminary cage design and to find an optimal value of filling density for 3D printing process. Surface characterisation confirmed a uniform coating of nHAp with nanoscale topography. Mechanical evaluation showed mechanical properties of final cage design similar to that of trabecular bone. Preliminary cell culture results showed promising results in terms of cell growth and activity confirming biocompatibility of constructs. Thus for the first time, design optimisation based on computational and experimental analysis combined with the 3D-printing technique for intervertebral fusion cage has been reported in a single study. 3D-printing is a promising technique for medical applications and this study paves the way for future development of customised implants in spinal

  9. Simplified Decoding of Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Truong, T. K.; Reed, I. S.

    1986-01-01

    Some complicated intermediate steps shortened or eliminated. Decoding of convolutional error-correcting digital codes simplified by new errortrellis syndrome technique. In new technique, syndrome vector not computed. Instead, advantage taken of newly-derived mathematical identities simplify decision tree, folding it back on itself into form called "error trellis." This trellis graph of all path solutions of syndrome equations. Each path through trellis corresponds to specific set of decisions as to received digits. Existing decoding algorithms combined with new mathematical identities reduce number of combinations of errors considered and enable computation of correction vector directly from data and check bits as received.

  10. Fabrication of geometric sapphire shaped InGaN/Al2O3 (S) LED scribed by using wet chemical etching

    NASA Astrophysics Data System (ADS)

    Kawan, Anil; Yu, S. J.; Park, Hwa Jin; Seo, Ju-Ok; Yoon, Seok-Beom

    2014-02-01

    The wet chemical etching method for etching V-grooves into sapphire substrates is used as scribing technique, and a geometric sapphire shaped InGaN/Al2O3 (S) light-emitting diode (LED) chip is fabricated. The V-groove is formed on the backside of a 150-µ-thick sapphire substrate by wet etching in a 3H2SO4:1H3PO4 chemical solution. The fabricated wet scribed geometric sapphire shaped LED exhibits a 15.86% enhancement in the light output power at 60-mA compared to the laser-stealth-scribed conventional rectangular LED. In addition, a ray-tracing simulation using "Light Tools" is performed on shaped geometric sapphire samples to investigate the enhancement of the light extracted from the substrate. The enhancement of the light output power for the wetscribed geometric sapphire shaped LED is thought to be due to the elimination of thermal damage and to an increase in light extraction from geometric sapphire shaped structure.

  11. Rapid fabrication of SERS substrate and superhydrophobic surface with different micro/nano-structures by electrochemical shaping of smooth Cu surface

    NASA Astrophysics Data System (ADS)

    Guo, Manman; Liu, Meili; Zhao, Wei; Xia, Yue; Huang, Wei; Li, Zelin

    2015-10-01

    Direct electrochemical shaping of metal surfaces into micro/nano-structures with desired functions is interesting and attractive. In this work, we employed square wave potential pulses (SWPP) to shape a smooth Cu surface into micro/nano-structures efficiently in a blank H2SO4 solution. Delightedly, we obtained Cu sub-micrometric islands on the surface with very strong surface enhanced Raman scattering (SERS) effect in 5 s, and fabricated a coral-like micro/nano-structured copper film with superhydrophobicity in 40 s. This method is green, facile, fast, and easy to control.

  12. Fabrication of transparent, tough, and conductive shape-memory polyurethane films by incorporating a small amount of high-quality graphene.

    PubMed

    Jung, Yong Chae; Kim, Jin Hee; Hayashi, Takuya; Kim, Yoong Ahm; Endo, Morinobu; Terrones, Mauricio; Dresselhaus, Mildred S

    2012-04-23

    We report a mechanically strong, electrically and thermally conductive, and optically transparent shape-memory polyurethane composite which was fabricated by introducing a small amount (0.1 wt%) of high-quality graphene as a filler. Geometrically large (≈4.6 μm(2)), but highly crystallized few-layer graphenes, verified by Raman spectroscopy and transmission electron microscopy, were prepared by the sonication of expandable graphite in an organic solvent. Oxygen- containing functional groups at the edge plane of graphene were crucial for an effective stress transfer from the graphene to polyurethane. Homogeneously dispersed few-layered graphene enabled polyurethane to have a high shape recovery force of 1.8 MPa cm(-3). Graphene, which is intrinsically stretchable up to 10%, will enable high-performance composites to be fabricated at relatively low cost and we thus envisage that such composites may replace carbon nanotubes for various applications in the near future.

  13. The trellis complexity of convolutional codes

    NASA Technical Reports Server (NTRS)

    Mceliece, R. J.; Lin, W.

    1995-01-01

    It has long been known that convolutional codes have a natural, regular trellis structure that facilitates the implementation of Viterbi's algorithm. It has gradually become apparent that linear block codes also have a natural, though not in general a regular, 'minimal' trellis structure, which allows them to be decoded with a Viterbi-like algorithm. In both cases, the complexity of the Viterbi decoding algorithm can be accurately estimated by the number of trellis edges per encoded bit. It would, therefore, appear that we are in a good position to make a fair comparison of the Viterbi decoding complexity of block and convolutional codes. Unfortunately, however, this comparison is somewhat muddled by the fact that some convolutional codes, the punctured convolutional codes, are known to have trellis representations that are significantly less complex than the conventional trellis. In other words, the conventional trellis representation for a convolutional code may not be the minimal trellis representation. Thus, ironically, at present we seem to know more about the minimal trellis representation for block than for convolutional codes. In this article, we provide a remedy, by developing a theory of minimal trellises for convolutional codes. (A similar theory has recently been given by Sidorenko and Zyablov). This allows us to make a direct performance-complexity comparison for block and convolutional codes. A by-product of our work is an algorithm for choosing, from among all generator matrices for a given convolutional code, what we call a trellis-minimal generator matrix, from which the minimal trellis for the code can be directly constructed. Another by-product is that, in the new theory, punctured convolutional codes no longer appear as a special class, but simply as high-rate convolutional codes whose trellis complexity is unexpectedly small.

  14. Dip TIPS as a facile and versatile method for fabrication of polymer foams with controlled shape, size and pore architecture for bioengineering applications.

    PubMed

    Kasoju, Naresh; Kubies, Dana; Kumorek, Marta M; Kříž, Jan; Fábryová, Eva; Machová, Lud'ka; Kovářová, Jana; Rypáček, František

    2014-01-01

    The porous polymer foams act as a template for neotissuegenesis in tissue engineering, and, as a reservoir for cell transplants such as pancreatic islets while simultaneously providing a functional interface with the host body. The fabrication of foams with the controlled shape, size and pore structure is of prime importance in various bioengineering applications. To this end, here we demonstrate a thermally induced phase separation (TIPS) based facile process for the fabrication of polymer foams with a controlled architecture. The setup comprises of a metallic template bar (T), a metallic conducting block (C) and a non-metallic reservoir tube (R), connected in sequence T-C-R. The process hereinafter termed as Dip TIPS, involves the dipping of the T-bar into a polymer solution, followed by filling of the R-tube with a freezing mixture to induce the phase separation of a polymer solution in the immediate vicinity of T-bar; Subsequent free-drying or freeze-extraction steps produced the polymer foams. An easy exchange of the T-bar of a spherical or rectangular shape allowed the fabrication of tubular, open- capsular and flat-sheet shaped foams. A mere change in the quenching time produced the foams with a thickness ranging from hundreds of microns to several millimeters. And, the pore size was conveniently controlled by varying either the polymer concentration or the quenching temperature. Subsequent in vivo studies in brown Norway rats for 4-weeks demonstrated the guided cell infiltration and homogenous cell distribution through the polymer matrix, without any fibrous capsule and necrotic core. In conclusion, the results show the "Dip TIPS" as a facile and adaptable process for the fabrication of anisotropic channeled porous polymer foams of various shapes and sizes for potential applications in tissue engineering, cell transplantation and other related fields.

  15. Dip TIPS as a Facile and Versatile Method for Fabrication of Polymer Foams with Controlled Shape, Size and Pore Architecture for Bioengineering Applications

    PubMed Central

    Kasoju, Naresh; Kubies, Dana; Kumorek, Marta M.; Kříž, Jan; Fábryová, Eva; Machová, Lud'ka; Kovářová, Jana; Rypáček, František

    2014-01-01

    The porous polymer foams act as a template for neotissuegenesis in tissue engineering, and, as a reservoir for cell transplants such as pancreatic islets while simultaneously providing a functional interface with the host body. The fabrication of foams with the controlled shape, size and pore structure is of prime importance in various bioengineering applications. To this end, here we demonstrate a thermally induced phase separation (TIPS) based facile process for the fabrication of polymer foams with a controlled architecture. The setup comprises of a metallic template bar (T), a metallic conducting block (C) and a non-metallic reservoir tube (R), connected in sequence T-C-R. The process hereinafter termed as Dip TIPS, involves the dipping of the T-bar into a polymer solution, followed by filling of the R-tube with a freezing mixture to induce the phase separation of a polymer solution in the immediate vicinity of T-bar; Subsequent free-drying or freeze-extraction steps produced the polymer foams. An easy exchange of the T-bar of a spherical or rectangular shape allowed the fabrication of tubular, open- capsular and flat-sheet shaped foams. A mere change in the quenching time produced the foams with a thickness ranging from hundreds of microns to several millimeters. And, the pore size was conveniently controlled by varying either the polymer concentration or the quenching temperature. Subsequent in vivo studies in brown Norway rats for 4-weeks demonstrated the guided cell infiltration and homogenous cell distribution through the polymer matrix, without any fibrous capsule and necrotic core. In conclusion, the results show the “Dip TIPS” as a facile and adaptable process for the fabrication of anisotropic channeled porous polymer foams of various shapes and sizes for potential applications in tissue engineering, cell transplantation and other related fields. PMID:25275373

  16. Convolution-deconvolution in DIGES

    SciTech Connect

    Philippacopoulos, A.J.; Simos, N.

    1995-05-01

    Convolution and deconvolution operations is by all means a very important aspect of SSI analysis since it influences the input to the seismic analysis. This paper documents some of the convolution/deconvolution procedures which have been implemented into the DIGES code. The 1-D propagation of shear and dilatational waves in typical layered configurations involving a stack of layers overlying a rock is treated by DIGES in a similar fashion to that of available codes, e.g. CARES, SHAKE. For certain configurations, however, there is no need to perform such analyses since the corresponding solutions can be obtained in analytic form. Typical cases involve deposits which can be modeled by a uniform halfspace or simple layered halfspaces. For such cases DIGES uses closed-form solutions. These solutions are given for one as well as two dimensional deconvolution. The type of waves considered include P, SV and SH waves. The non-vertical incidence is given special attention since deconvolution can be defined differently depending on the problem of interest. For all wave cases considered, corresponding transfer functions are presented in closed-form. Transient solutions are obtained in the frequency domain. Finally, a variety of forms are considered for representing the free field motion both in terms of deterministic as well as probabilistic representations. These include (a) acceleration time histories, (b) response spectra (c) Fourier spectra and (d) cross-spectral densities.

  17. Fabrication and characterization of a foamed polylactic acid (PLA)/ thermoplastic polyurethane (TPU) shape memory polymer (SMP) blend for biomedical and clinical applications

    NASA Astrophysics Data System (ADS)

    Song, Janice J.; Srivastava, Ijya; Kowalski, Jennifer; Naguib, Hani E.

    2014-03-01

    Shape memory polymers (SMP) are a class of stimuli-responsive materials that are able to respond to external stimulus such as heat by altering their shape. Bio-compatible SMPs have a number of advantages over static materials and are being studied extensively for biomedical and clinical applications (such as tissue stents and scaffolds). A previous study has demonstrated that the bio-compatible polymer blend of polylactic acid (PLA)/ thermoplastic polyurethane (TPU) (50/50 and 70/30) exhibit good shape memory properties. In this study, the mechanical and thermo-mechanical (shape memory) properties of TPU/PLA SMP blends were characterized; the compositions studied were 80/20, 65/35, and 50/50 TPU/PLA. In addition, porous TPU/PLA SMP blends were fabricated with a gas-foaming technique; and the morphology of the porous structure of these SMPs foams were characterized with scanning electron microscopy (SEM). The TPU/PLA bio-compatible SMP blend was fabricated with melt-blending and compression molding. The glass transition temperature (Tg) of the SMP blends was determined with a differential scanning calorimeter (DSC). The mechanical properties studied were the stress-strain behavior, tensile strength, and elastic modulus; and the thermomechanical (or shape memory) properties studied were the shape fixity rate (Rf), shape recovery rate (Rr), response time, and the effect of recovery temperature on Rr. The porous 80/20 PLA/TPU SMP blend was found to have the highest tensile strength, toughness and percentage extension, as well as the lowest density and uniform pore structure in the micron and submicron scale. The porous 80/20 TPU/PLA SMP blend may be further developed for specific biomedical and clinical applications where a combination of tensile strength, toughness, and low density are required.

  18. Modified cubic convolution resampling for Landsat

    NASA Technical Reports Server (NTRS)

    Prakash, A.; Mckee, B.

    1985-01-01

    An overview is given of Landsat Thematic Mapper resampling technique, including a modification of the well-known cubic convolution interpolator (nearest neighbor interpolation) used to provide geometric correction for TM data. Post launch study has shown that the modified cubic convolution interpolator can selectively enhance or suppress frequency bands in the output image. This selectivity is demonstrated on TM Band 3 imagery.

  19. The general theory of convolutional codes

    NASA Technical Reports Server (NTRS)

    Mceliece, R. J.; Stanley, R. P.

    1993-01-01

    This article presents a self-contained introduction to the algebraic theory of convolutional codes. This introduction is partly a tutorial, but at the same time contains a number of new results which will prove useful for designers of advanced telecommunication systems. Among the new concepts introduced here are the Hilbert series for a convolutional code and the class of compact codes.

  20. Achieving unequal error protection with convolutional codes

    NASA Technical Reports Server (NTRS)

    Mills, D. G.; Costello, D. J., Jr.; Palazzo, R., Jr.

    1994-01-01

    This paper examines the unequal error protection capabilities of convolutional codes. Both time-invariant and periodically time-varying convolutional encoders are examined. The effective free distance vector is defined and is shown to be useful in determining the unequal error protection (UEP) capabilities of convolutional codes. A modified transfer function is used to determine an upper bound on the bit error probabilities for individual input bit positions in a convolutional encoder. The bound is heavily dependent on the individual effective free distance of the input bit position. A bound relating two individual effective free distances is presented. The bound is a useful tool in determining the maximum possible disparity in individual effective free distances of encoders of specified rate and memory distribution. The unequal error protection capabilities of convolutional encoders of several rates and memory distributions are determined and discussed.

  1. Search for optimal distance spectrum convolutional codes

    NASA Technical Reports Server (NTRS)

    Connor, Matthew C.; Perez, Lance C.; Costello, Daniel J., Jr.

    1993-01-01

    In order to communicate reliably and to reduce the required transmitter power, NASA uses coded communication systems on most of their deep space satellites and probes (e.g. Pioneer, Voyager, Galileo, and the TDRSS network). These communication systems use binary convolutional codes. Better codes make the system more reliable and require less transmitter power. However, there are no good construction techniques for convolutional codes. Thus, to find good convolutional codes requires an exhaustive search over the ensemble of all possible codes. In this paper, an efficient convolutional code search algorithm was implemented on an IBM RS6000 Model 580. The combination of algorithm efficiency and computational power enabled us to find, for the first time, the optimal rate 1/2, memory 14, convolutional code.

  2. Three-Dimensional Grain Shape-Fabric from Unconsolidated Pyroclastic Density Current Deposits: Implications for Extracting Flow Direction and Insights on Rheology

    NASA Astrophysics Data System (ADS)

    Hawkins, T. T.; Brand, B. D.; Sarrochi, D.; Pollock, N.

    2016-12-01

    One of the greatest challenges volcanologists face is the ability to extrapolate information about eruption dynamics and emplacement conditions from deposits. Pyroclastic density current (PDC) deposits are particularly challenging given the wide range of initial current conditions, (e.g., granular, fluidized, concentrated, dilute), and rapid flow transformations due to interaction with evolving topography. Analysis of particle shape-fabric can be used to determine flow direction, and may help to understand the rheological characteristics of the flows. However, extracting shape-fabric information from outcrop (2D) apparent fabric is limited, especially when outcrop exposure is incomplete or lacks context. To better understand and quantify the complex flow dynamics reflected in PDC deposits, we study the complete shape-fabric data in 3D using oriented samples. In the field, the prospective sample is carved from the unconsolidated deposit in blocks, the dimensions of which depend on the average clast size in the sample. The sample is saturated in situ with a water-based sodium silicate solution, then wrapped in plaster-soaked gauze to form a protective cast. The orientation of the sample is recorded on the block faces. The samples dry for five days and are then extracted in intact blocks. In the lab, the sample is vacuum impregnated with sodium silicate and cured in an oven. The fully lithified sample is first cut along the plan view to identify orientations of the long axes of the grains (flow direction), and then cut in the two plains perpendicular to grain elongation. 3D fabric analysis is performed using high resolution images of the cut-faces using computer assisted image analysis software devoted to shape-fabric analysis. Here we present the results of samples taken from the 18 May 1980 PDC deposit facies, including massive, diffuse-stratified and cross-stratified lapilli tuff. We show a relationship between the strength of iso-orientation of the elongated

  3. Two-dimensional cubic convolution.

    PubMed

    Reichenbach, Stephen E; Geng, Frank

    2003-01-01

    The paper develops two-dimensional (2D), nonseparable, piecewise cubic convolution (PCC) for image interpolation. Traditionally, PCC has been implemented based on a one-dimensional (1D) derivation with a separable generalization to two dimensions. However, typical scenes and imaging systems are not separable, so the traditional approach is suboptimal. We develop a closed-form derivation for a two-parameter, 2D PCC kernel with support [-2,2] x [-2,2] that is constrained for continuity, smoothness, symmetry, and flat-field response. Our analyses, using several image models, including Markov random fields, demonstrate that the 2D PCC yields small improvements in interpolation fidelity over the traditional, separable approach. The constraints on the derivation can be relaxed to provide greater flexibility and performance.

  4. Recent Advances in Near-Net-Shape Fabrication of Al-Li Alloy 2195 for Launch Vehicles

    NASA Technical Reports Server (NTRS)

    Wagner, John; Domack, Marcia; Hoffman, Eric

    2007-01-01

    Recent applications in launch vehicles use 2195 processed to Super Lightweight Tank specifications. Potential benefits exist by tailoring heat treatment and other processing parameters to the application. Assess the potential benefits and advocate application of Al-Li near-net-shape technologies for other launch vehicle structural components. Work with manufacturing and material producers to optimize Al-Li ingot shape and size for enhanced near-net-shape processing. Examine time dependent properties of 2195 critical for reusable applications.

  5. Differences in the thickness of mouthguards fabricated from ethylene vinyl acetate copolymer sheets with differently arranged v-shaped grooves: part 2 - effect of shape on the working model.

    PubMed

    Takahashi, Mutsumi; Koide, Kaoru; Mizuhashi, Fumi

    2014-12-01

    The aim of this study was to evaluate the change in thickness of a working model mouthguard sheet due to different shape. Mouthguards were fabricated with ethylene vinyl acetate (EVA) sheets (4.0 mm thick) using a vacuum-forming machine. Two shapes of the sheet were compared: normal sheet or v-shaped groove 10-40 mm from the anterior end. Additionally, two shapes of the working model were compared; the basal plane was vertical to the tooth axis of the maxillary central incisor (condition A), and the occlusal plane was parallel to the basal plane (condition B). Sheets were heated until they sagged 15 mm below the clamp. Postmolding thickness was determined for the incisal portion (incisal edge and labial surface) and molar portion (cusp and buccal surface). Differences in the change in thickness due to the shape of the sheets and model were analyzed using two-way anova followed by a Bonferroni's multiple comparison tests. The thickness of the mouthguard sheet with v-shaped grooves was more than that of the normal sheet at all measuring points under condition A and condition B (P < 0.01). The thickness of condition B was less than that of condition A, there the incisal portion in the normal sheet and the incisal edge in the sheet with v-shaped grooves (P < 0.01). The present results suggested that thickness after molding was secured by the use of the sheet with v-shaped grooves. In particular, the model with the undercut on the labial surface may be clinically useful.

  6. Constructing Parton Convolution in Effective Field Theory

    SciTech Connect

    Chen, Jiunn-Wei; Ji, Xiangdong

    2001-10-08

    Parton convolution models have been used extensively in describing the sea quarks in the nucleon and explaining quark distributions in nuclei (the EMC effect). From the effective field theory point of view, we construct the parton convolution formalism which has been the underlying conception of all convolution models. We explain the significance of scheme and scale dependence of the auxiliary quantities such as the pion distributions in a nucleon. As an application, we calculate the complete leading nonanalytic chiral contribution to the isovector component of the nucleon sea.

  7. Mask-free, vacuum-free fabrication of high-conductivity metallic nanowire by spatially shaped ultrafast laser (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Wang, Andong; Li, Xiaowei; Qu, Lianti; Lu, Yongfeng; Jiang, Lan

    2017-03-01

    Metal nanowire fabrication has drawn tremendous attention in recent years due to its wide application in electronics, optoelectronics, and plasmonics. However, conventional laser fabrication technologies are limited by diffraction limit thus the fabrication resolution cannot meet the increasingly high demand of modern devices. Herein we report on a novel method for high-resolution high-quality metal nanowire fabrication by using Hermite-Gaussian beam to ablate metal thin film. The nanowire is formed due to the intensity valley in the center of the laser beam while the surrounding film is ablated. Arbitrary nanowire can be generated on the substrate by dynamically adjusting the orientation of the intensity valley. This method shows obvious advantages compared to conventional methods. First, the minimum nanowire has a width of 60 nm (≍1/13 of the laser wavelength), which is much smaller than the diffraction limit. The high resolution is achieved by combining the ultrashort nature of the femtosecond laser and the low thermal conductivity of the thin film. In addition, the fabricated nanowires have good inside qualities. No inner nanopores and particle intervals are generated inside the nanowire, thus endowing the nanowire with good electronic characteristics: the conductivity of the nanowires is as high as 1.2×107 S/m (≍1/4 of buck material), and the maximum current density is up to 1.66×108 A/m2. Last, the nanowire has a good adhesion to the substrates, which can withstand ultrasonic bath for a long time. These advantages make our method a good approach for high-resolution high-quality nanowire fabrication as a complementary method to conventional lithography methods.

  8. NRZ Data Asymmetry Corrector and Convolutional Encoder

    NASA Technical Reports Server (NTRS)

    Pfiffner, H. J.

    1983-01-01

    Circuit compensates for timing, amplitude and symmetry perturbations. Data asymmetry corrector and convolutional encoder regenerate data and clock signals in spite of signal variations such as data or clock asymmetry, phase errors, and amplitude variations, then encode data for transmission.

  9. Parallel architectures for computing cyclic convolutions

    NASA Technical Reports Server (NTRS)

    Yeh, C.-S.; Reed, I. S.; Truong, T. K.

    1983-01-01

    In the paper two parallel architectural structures are developed to compute one-dimensional cyclic convolutions. The first structure is based on the Chinese remainder theorem and Kung's pipelined array. The second structure is a direct mapping from the mathematical definition of a cyclic convolution to a computational architecture. To compute a d-point cyclic convolution the first structure needs d/2 inner product cells, while the second structure and Kung's linear array require d cells. However, to compute a cyclic convolution, the second structure requires less time than both the first structure and Kung's linear array. Another application of the second structure is to multiply a Toeplitz matrix by a vector. A table is listed to compare these two structures and Kung's linear array. Both structures are simple and regular and are therefore suitable for VLSI implementation.

  10. Parallel architectures for computing cyclic convolutions

    NASA Technical Reports Server (NTRS)

    Yeh, C.-S.; Reed, I. S.; Truong, T. K.

    1983-01-01

    In the paper two parallel architectural structures are developed to compute one-dimensional cyclic convolutions. The first structure is based on the Chinese remainder theorem and Kung's pipelined array. The second structure is a direct mapping from the mathematical definition of a cyclic convolution to a computational architecture. To compute a d-point cyclic convolution the first structure needs d/2 inner product cells, while the second structure and Kung's linear array require d cells. However, to compute a cyclic convolution, the second structure requires less time than both the first structure and Kung's linear array. Another application of the second structure is to multiply a Toeplitz matrix by a vector. A table is listed to compare these two structures and Kung's linear array. Both structures are simple and regular and are therefore suitable for VLSI implementation.

  11. Utilization of low-redundancy convolutional codes

    NASA Technical Reports Server (NTRS)

    Cain, J. B.

    1973-01-01

    This paper suggests guidelines for the utilization of low-redundancy convolutional codes with emphasis on providing a quick look capability (no decoding) and a moderate amount of coding gain. The performance and implementation complexity of threshold, Viterbi, and sequential decoding when used with low-redundancy, systematic, convolutional codes is discussed. An extensive list of optimum, short constraint length codes is found for use with Viterbi decoding, and several good, long constraint length codes are found for use with sequential decoding.

  12. A note on cubic convolution interpolation.

    PubMed

    Meijering, Erik; Unser, Michael

    2003-01-01

    We establish a link between classical osculatory interpolation and modern convolution-based interpolation and use it to show that two well-known cubic convolution schemes are formally equivalent to two osculatory interpolation schemes proposed in the actuarial literature about a century ago. We also discuss computational differences and give examples of other cubic interpolation schemes not previously studied in signal and image processing.

  13. Coset Codes Viewed as Terminated Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Fossorier, Marc P. C.; Lin, Shu

    1996-01-01

    In this paper, coset codes are considered as terminated convolutional codes. Based on this approach, three new general results are presented. First, it is shown that the iterative squaring construction can equivalently be defined from a convolutional code whose trellis terminates. This convolutional code determines a simple encoder for the coset code considered, and the state and branch labelings of the associated trellis diagram become straightforward. Also, from the generator matrix of the code in its convolutional code form, much information about the trade-off between the state connectivity and complexity at each section, and the parallel structure of the trellis, is directly available. Based on this generator matrix, it is shown that the parallel branches in the trellis diagram of the convolutional code represent the same coset code C(sub 1), of smaller dimension and shorter length. Utilizing this fact, a two-stage optimum trellis decoding method is devised. The first stage decodes C(sub 1), while the second stage decodes the associated convolutional code, using the branch metrics delivered by stage 1. Finally, a bidirectional decoding of each received block starting at both ends is presented. If about the same number of computations is required, this approach remains very attractive from a practical point of view as it roughly doubles the decoding speed. This fact is particularly interesting whenever the second half of the trellis is the mirror image of the first half, since the same decoder can be implemented for both parts.

  14. Frequency domain convolution for SCANSAR

    NASA Astrophysics Data System (ADS)

    Cantraine, Guy; Dendal, Didier

    1994-12-01

    Starting from basic signals expressions, the rigorous formulation of frequency domain convolution is demonstrated, in general and impulse terms, including antenna patterns and squint angle. The major differences with conventional algorithms are discussed and theoretical concepts clarified. In a second part, the philosophy of advanced SAR algorithms is compared with that of a SCANSAR observation (several subswaths). It is proved that a general impulse response can always be written as the product of three factors, i.e., a phasor, an antenna coefficient, and a migration expression, and that the details of antenna effects can be ignored in the usual SAR system, but not the range migration (the situation is reversed in a SCANSAR reconstruction scheme). In a next step, some possible inverse filter kernels (the matched filter, the true inverse filter, ...) for general SAR or SCANSAR mode reconstructions, are compared. By adopting a noise corrupted model of data, we get the corresponding Wiener filter, the major interest of which is to avoid all divergence risk. Afterwards, the vocable `a class of filter' is introduced and summarized by a parametric formulation. Lastly, the homogeneity of the reconstruction, with a noncyclic fast Fourier transform deconvolution is studied by comparing peak responses according to the burst location. The more homogeneous sensitivity of the Wiener filter, with a stepper fall when the target begins to go outside the antenna pattern, is confirmed. A linear optimal merging of adjacent looks (in azimuth) minimizing the rms noise is also presented, as well as consideration about squint ambiguity.

  15. Design and fabrication of a novel XYθz monolithic micro-positioning stage driven by NiTi shape-memory-alloy actuators

    NASA Astrophysics Data System (ADS)

    AbuZaiter, Alaa; Faris Hikmat, Omer; Nafea, Marwan; Ali, Mohamed Sultan Mohamed

    2016-10-01

    This paper reports a new shape-memory-alloy (SMA) micro-positioning stage. The device has been monolithically micro-machined with a single fabrication step. The design comprises a moving stage that is manipulated by six SMA planar springs actuators to generate movements with three degrees of freedom. The overall design is square in shape and has dimensions of 12 mm × 12 mm × 0.25 mm. Localized thermomechanical training for shape setting of SMA planar springs was performed using electrical current induced heating at restrained condition to individually train each of the six actuators to memorize a predetermined shape. For actuation, each SMA actuator is individually driven using Joule heating induced by an electrical current. The current flow is controlled by an external pulse-width modulation signal. The thermal response and heat distribution were simulated and experimentally verified using infrared imaging. The micro-positioning results indicated maximum stage movements of 1.2 and 1.6 mm along the x- and y-directions, respectively. Rotational movements were also demonstrated with a total range of 20°. The developed micro-positioning device has been successfully used to move a small object for microscopic scanning applications.

  16. Cell differentiation on disk- and string-shaped hydrogels fabricated from Ca(2+) -responsive self-assembling peptides.

    PubMed

    Fukunaga, Kazuto; Tsutsumi, Hiroshi; Mihara, Hisakazu

    2016-11-04

    We recently developed a self-assembling peptide, E1Y9, that self-assembles into nanofibers and forms a hydrogel in the presence of Ca(2+) . E1Y9 derivatives conjugated with functional peptide sequences derived from extracellular matrices (ECMs) reportedly self-assemble into peptide nanofibers that enhance cell adhesion and differentiation. In this study, E1Y9/E1Y9-IKVAV-mixed hydrogels were constructed to serve as artificial ECMs that promote cell differentiation. E1Y9 and E1Y9-IKVAV co-assembled into networked nanofibers, and hydrogels with disk and string shapes were formed in response to Ca(2+) treatment. The neuronal differentiation of PC12 cells was facilitated on hydrogels of both shapes that contained the IKVAV motifs. Moreover, long neurites extended along the long axis of the string-shaped gel, suggesting that the structure of hydrogels of this shape can affect cellular orientation. Thus, E1Y9 hydrogels can potentially be used as artificial ECMs with desirable bioactivities and shapes that could be useful in tissue engineering applications. © 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 476-483, 2016. © 2015 Wiley Periodicals, Inc.

  17. Anatomically informed convolution kernels for the projection of fMRI data on the cortical surface.

    PubMed

    Operto, Grégory; Bulot, Rémy; Anton, Jean-Luc; Coulon, Olivier

    2006-01-01

    We present here a method that aims at producing representations of functional brain data on the cortical surface from functional MRI volumes. Such representations are required for subsequent cortical-based functional analysis. We propose a projection technique based on the definition, around each node of the grey/white matter interface mesh, of convolution kernels whose shape and distribution rely on the geometry of the local anatomy. For one anatomy, a set of convolution kernels is computed that can be used to project any functional data registered with this anatomy. The method is presented together with experiments on synthetic data and real statistical t-maps.

  18. Trainable Convolution Filters and Their Application to Face Recognition.

    PubMed

    Kumar, Ritwik; Banerjee, Arunava; Vemuri, Baba C; Pfister, Hanspeter

    2012-07-01

    In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system treats images as a collection of possibly overlapping patches and is composed of three components: (1) A scheme for a single patch classification that seeks a smooth, possibly nonlinear, functional mapping of the patches into a range space, where patches of the same class are close to one another, while patches from different classes are far apart-in the L_2 sense. This mapping is accomplished using trainable convolution filters (or Volterra kernels) where the convolution kernel can be of any shape or order. (2) Given a corpus of Volterra classifiers with various kernel orders and shapes for each patch, a boosting scheme for automatically selecting the best weighted combination of the classifiers to achieve higher per-patch classification rate. (3) A scheme for aggregating the classification information obtained for each patch via voting for the parent image classification. We demonstrate the effectiveness of the proposed technique using face recognition as an application area and provide extensive experiments on the Yale, CMU PIE, Extended Yale B, Multi-PIE, and MERL Dome benchmark face data sets. We call the Volterra kernel classifiers applied to face recognition Volterrafaces. We show that our technique, which falls into the broad class of embedding-based face image discrimination methods, consistently outperforms various state-of-the-art methods in the same category.

  19. Correction of the tip convolution effects in the imaging of nanostructures studied through scanning force microscopy.

    PubMed

    Canet-Ferrer, Josep; Coronado, Eugenio; Forment-Aliaga, Alicia; Pinilla-Cienfuegos, Elena

    2014-10-03

    AFM images are always affected by artifacts arising from tip convolution effects, resulting in a decrease in the lateral resolution of this technique. The magnitude of such effects is described by means of geometrical considerations, thereby providing better understanding of the convolution phenomenon. We demonstrate that for a constant tip radius, the convolution error is increased with the object height, mainly for the narrowest motifs. Certain influence of the object shape is observed between rectangular and elliptical objects with the same height. Such moderate differences are essentially expected among elongated objects; in contrast they are reduced as the object aspect ratio is increased. Finally, we propose an algorithm to study the influence of the size, shape and aspect ratio of different nanometric motifs on a flat substrate. Indeed, with this algorithm, convolution artifacts can be extended to any kind of motif including real surface roughness. From the simulation results we demonstrate that in most cases the real motif's width can be estimated from AFM images without knowing its shape in detail.

  20. Precise two-dimensional D-bar reconstructions of human chest and phantom tank via sinc-convolution algorithm.

    PubMed

    Abbasi, Mahdi; Naghsh-Nilchi, Ahmad-Reza

    2012-06-20

    Electrical Impedance Tomography (EIT) is used as a fast clinical imaging technique for monitoring the health of the human organs such as lungs, heart, brain and breast. Each practical EIT reconstruction algorithm should be efficient enough in terms of convergence rate, and accuracy. The main objective of this study is to investigate the feasibility of precise empirical conductivity imaging using a sinc-convolution algorithm in D-bar framework. At the first step, synthetic and experimental data were used to compute an intermediate object named scattering transform. Next, this object was used in a two-dimensional integral equation which was precisely and rapidly solved via sinc-convolution algorithm to find the square root of the conductivity for each pixel of image. For the purpose of comparison, multigrid and NOSER algorithms were implemented under a similar setting. Quality of reconstructions of synthetic models was tested against GREIT approved quality measures. To validate the simulation results, reconstructions of a phantom chest and a human lung were used. Evaluation of synthetic reconstructions shows that the quality of sinc-convolution reconstructions is considerably better than that of each of its competitors in terms of amplitude response, position error, ringing, resolution and shape-deformation. In addition, the results confirm near-exponential and linear convergence rates for sinc-convolution and multigrid, respectively. Moreover, the least degree of relative errors and the most degree of truth were found in sinc-convolution reconstructions from experimental phantom data. Reconstructions of clinical lung data show that the related physiological effect is well recovered by sinc-convolution algorithm. Parametric evaluation demonstrates the efficiency of sinc-convolution to reconstruct accurate conductivity images from experimental data. Excellent results in phantom and clinical reconstructions using sinc-convolution support parametric assessment results

  1. Precise two-dimensional D-bar reconstructions of human chest and phantom tank via sinc-convolution algorithm

    PubMed Central

    2012-01-01

    Background Electrical Impedance Tomography (EIT) is used as a fast clinical imaging technique for monitoring the health of the human organs such as lungs, heart, brain and breast. Each practical EIT reconstruction algorithm should be efficient enough in terms of convergence rate, and accuracy. The main objective of this study is to investigate the feasibility of precise empirical conductivity imaging using a sinc-convolution algorithm in D-bar framework. Methods At the first step, synthetic and experimental data were used to compute an intermediate object named scattering transform. Next, this object was used in a two-dimensional integral equation which was precisely and rapidly solved via sinc-convolution algorithm to find the square root of the conductivity for each pixel of image. For the purpose of comparison, multigrid and NOSER algorithms were implemented under a similar setting. Quality of reconstructions of synthetic models was tested against GREIT approved quality measures. To validate the simulation results, reconstructions of a phantom chest and a human lung were used. Results Evaluation of synthetic reconstructions shows that the quality of sinc-convolution reconstructions is considerably better than that of each of its competitors in terms of amplitude response, position error, ringing, resolution and shape-deformation. In addition, the results confirm near-exponential and linear convergence rates for sinc-convolution and multigrid, respectively. Moreover, the least degree of relative errors and the most degree of truth were found in sinc-convolution reconstructions from experimental phantom data. Reconstructions of clinical lung data show that the related physiological effect is well recovered by sinc-convolution algorithm. Conclusions Parametric evaluation demonstrates the efficiency of sinc-convolution to reconstruct accurate conductivity images from experimental data. Excellent results in phantom and clinical reconstructions using sinc-convolution

  2. Hydrothermal fabrication of octahedral-shaped Fe{sub 3}O{sub 4} nanoparticles and their magnetorheological response

    SciTech Connect

    Jung, H. S.; Choi, H. J.

    2015-05-07

    Octahedral-shaped Fe{sub 3}O{sub 4} nanoparticles were synthesized in the presence of 1,3-diaminopropane using a hydrothermal method and assessed as a potential magnetorheological (MR) material. Their morphology, crystal structure, and magnetic properties were examined by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and vibrating sample magnetometry, respectively. The MR characteristics of the octahedral-shaped, Fe{sub 3}O{sub 4} nanoparticle-based MR particles when dispersed in silicone oil with a 10 vol. % particle concentration were examined using a rotational rheometer under an external magnetic field. The resulting MR fluids exhibited a Bingham-like behavior with a distinctive yield stress from their flow curves.

  3. Interpolation by two-dimensional cubic convolution

    NASA Astrophysics Data System (ADS)

    Shi, Jiazheng; Reichenbach, Stephen E.

    2003-08-01

    This paper presents results of image interpolation with an improved method for two-dimensional cubic convolution. Convolution with a piecewise cubic is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional, separable method is sub-optimal for the usual case of non-separable images. The improved method in this paper implements the most general non-separable, two-dimensional, piecewise-cubic interpolator with constraints for symmetry, continuity, and smoothness. The improved method of two-dimensional cubic convolution has three parameters that can be tuned to yield maximal fidelity for specific scene ensembles characterized by autocorrelation or power-spectrum. This paper illustrates examples for several scene models (a circular disk of parametric size, a square pulse with parametric rotation, and a Markov random field with parametric spatial detail) and actual images -- presenting the optimal parameters and the resulting fidelity for each model. In these examples, improved two-dimensional cubic convolution is superior to several other popular small-kernel interpolation methods.

  4. Novel fabrication process for 3D meander-shaped microcoils in SU-8 dielectric and their application to linear micromotors

    NASA Astrophysics Data System (ADS)

    Seidemann, Volker; Buettgenbach, Stephanus

    2001-04-01

    This paper reports on an optimized fabrication process for three dimensional coil structures such as meander or helical coils wound around in plane magnetic structures. The process consists of UV depth lithography employing AZ4562 and SU8 photo resists and electroplating of copper and nickel-iron. Furthermore SU8 is used as the embedding dielectric due to its excellent planarization properties and high structural aspect ratio. Special emphasis was laid on the decrease of via interconnect resistance by electroplating the vias and upper conductors in a single step thus avoiding a large number of resistive interfaces. This was achieved by sacrificial wiring and structured seed layers. The developed technology is applied to a variable reluctance micro motor with a novel design that avoids high friction. The presented concept makes use of a stator traveler configuration generating complementary attraction forces. The technology and design concept is presented and first results are demonstrated.

  5. Uncertainty estimation by convolution using spatial statistics.

    PubMed

    Sanchez-Brea, Luis Miguel; Bernabeu, Eusebio

    2006-10-01

    Kriging has proven to be a useful tool in image processing since it behaves, under regular sampling, as a convolution. Convolution kernels obtained with kriging allow noise filtering and include the effects of the random fluctuations of the experimental data and the resolution of the measuring devices. The uncertainty at each location of the image can also be determined using kriging. However, this procedure is slow since, currently, only matrix methods are available. In this work, we compare the way kriging performs the uncertainty estimation with the standard statistical technique for magnitudes without spatial dependence. As a result, we propose a much faster technique, based on the variogram, to determine the uncertainty using a convolutional procedure. We check the validity of this approach by applying it to one-dimensional images obtained in diffractometry and two-dimensional images obtained by shadow moire.

  6. Astronomical Image Subtraction by Cross-Convolution

    NASA Astrophysics Data System (ADS)

    Yuan, Fang; Akerlof, Carl W.

    2008-04-01

    In recent years, there has been a proliferation of wide-field sky surveys to search for a variety of transient objects. Using relatively short focal lengths, the optics of these systems produce undersampled stellar images often marred by a variety of aberrations. As participants in such activities, we have developed a new algorithm for image subtraction that no longer requires high-quality reference images for comparison. The computational efficiency is comparable with similar procedures currently in use. The general technique is cross-convolution: two convolution kernels are generated to make a test image and a reference image separately transform to match as closely as possible. In analogy to the optimization technique for generating smoothing splines, the inclusion of an rms width penalty term constrains the diffusion of stellar images. In addition, by evaluating the convolution kernels on uniformly spaced subimages across the total area, these routines can accommodate point-spread functions that vary considerably across the focal plane.

  7. Molecular graph convolutions: moving beyond fingerprints

    PubMed Central

    Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

    2016-01-01

    Molecular “fingerprints” encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement. PMID:27558503

  8. Cyclic Cocycles on Twisted Convolution Algebras

    NASA Astrophysics Data System (ADS)

    Angel, Eitan

    2013-01-01

    We give a construction of cyclic cocycles on convolution algebras twisted by gerbes over discrete translation groupoids. For proper étale groupoids, Tu and Xu (Adv Math 207(2):455-483, 2006) provide a map between the periodic cyclic cohomology of a gerbe-twisted convolution algebra and twisted cohomology groups which is similar to the construction of Mathai and Stevenson (Adv Math 200(2):303-335, 2006). When the groupoid is not proper, we cannot construct an invariant connection on the gerbe; therefore to study this algebra, we instead develop simplicial techniques to construct a simplicial curvature 3-form representing the class of the gerbe. Then by using a JLO formula we define a morphism from a simplicial complex twisted by this simplicial curvature 3-form to the mixed bicomplex computing the periodic cyclic cohomology of the twisted convolution algebras.

  9. Molecular graph convolutions: moving beyond fingerprints.

    PubMed

    Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

    2016-08-01

    Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph-atoms, bonds, distances, etc.-which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.

  10. Molecular graph convolutions: moving beyond fingerprints

    NASA Astrophysics Data System (ADS)

    Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

    2016-08-01

    Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.

  11. Image reconstruction by parametric cubic convolution

    NASA Technical Reports Server (NTRS)

    Park, S. K.; Schowengerdt, R. A.

    1983-01-01

    Cubic convolution, which has been discussed by Rifman and McKinnon (1974), was originally developed for the reconstruction of Landsat digital images. In the present investigation, the reconstruction properties of the one-parameter family of cubic convolution interpolation functions are considered and thee image degradation associated with reasonable choices of this parameter is analyzed. With the aid of an analysis in the frequency domain it is demonstrated that in an image-independent sense there is an optimal value for this parameter. The optimal value is not the standard value commonly referenced in the literature. It is also demonstrated that in an image-dependent sense, cubic convolution can be adapted to any class of images characterized by a common energy spectrum.

  12. Manifestation of the shape-memory effect in polyetherurethane cellular plastics, fabric composites, and sandwich structures under microgravity

    NASA Astrophysics Data System (ADS)

    Babaevskii, P. G.; Kozlov, N. A.; Agapov, I. G.; Reznichenko, G. M.; Churilo, N. V.; Churilo, I. V.

    2016-09-01

    The results of experiments that were performed to test the feasibility of creating sandwich structures (consisting of thin-layer sheaths of polymer composites and a cellular polymer core) with the shapememory effect as models of the transformable components of space structures have been given. The data obtained indicate that samples of sandwich structures under microgravity conditions on board the International Space Station have recovered their shape to almost the same degree as under terrestrial conditions, which makes it possible to recommend them for creating components of transformable space structures on their basis.

  13. Multihop optical network with convolutional coding

    NASA Astrophysics Data System (ADS)

    Chien, Sufong; Takahashi, Kenzo; Prasad Majumder, Satya

    2002-01-01

    We evaluate the bit-error-rate (BER) performance of a multihop optical ShuffleNet with and without convolutional coding. Computed results show that there is considerable improvement in network performance resulting from coding in terms of an increased number of traversable hops from a given transmitter power at a given BER. For a rate-1/2 convolutional code with constraint length K = 9 at BER = 10-9, the hop gains are found to be 20 hops for hot-potato routing and 7 hops for single-buffer routing at the transmitter power of 0 dBm. We can further increase the hop gain by increasing transmitter power.

  14. Fast convolution algorithms for SAR processing

    NASA Astrophysics Data System (ADS)

    dall, Jorgen

    Most high resolution SAR processors apply the Fast Fourier Transform (FFT) to implement convolution by a matched filter impulse response. However, a lower computational complexity is attainable with other algorithms which accordingly have the potential of offering faster and/or simpler processors. Thirteen different fast transform and convolution algorithms are presented, and their characteristics are compared with the fundamental requirements imposed on the algorithms by various SAR processing schemes. The most promising algorithm is based on a Fermat Number Transform (FNT). SAR-580 and SEASAT SAR images have been successfully processed with the FNT, and in this connection the range curvature correction, noise properties and processing speed are discussed.

  15. An Observation of Diamond-Shaped Particle Structure in a Soya Phosphatidylcohline and Bacteriorhodopsin Composite Langmuir Blodgett Film Fabricated by Multilayer Molecular Thin Film Method

    NASA Astrophysics Data System (ADS)

    Tsujiuchi, Y.; Makino, Y.

    A composite film of soya phosphatidylcohline (soya PC) and bacteriorhodopsin (BR) was fabricated by the multilayer molecular thin film method using fatty acid and lipid on a quartz substrate. Direct Force Microscopy (DFM), UV absorption spectra and IR absorption spectra of the film were characterized on the detail of surface structure of the film. The DFM data revealed that many rhombus (diamond-shaped) particles were observed in the film. The spectroscopic data exhibited the yield of M-intermediate of BR in the film. On our modelling of molecular configuration indicate that the coexistence of the strong inter-molecular interaction and the strong inter-molecular interaction between BR trimmers attributed to form the particles.

  16. Fabrication of nano-imprint templates for dual-Damascene applications using a high resolution variable shape E-beam writer

    NASA Astrophysics Data System (ADS)

    Pritschow, Marcus; Butschke, Joerg; Irmscher, Mathias; Sailer, Holger; Resnick, Douglas; Thompson, Ecron

    2007-10-01

    A 3D template fabrication process has been developed, which enables the generation of high resolution, high aspect pillars on top of lines. These templates will be used to print both vias and metal lines at once for the dual damascene technology. Due to the complexity of state of the art CMOS designs only a variable shape e-beam (VSB) writer combined with chemically amplified resists (CAR) can be considered for the patterning process. We focused our work especially on the generation of high aspect pillars with a diameter below 50nm and the development of suitable overlay strategies for getting a precise alignment between the two template tiers. In this context we investigated the influence of exposure strategies on the overlay result across the entire imprint area of 25mm × 25mm. Finally, we realized templates according to the MII standard with different test designs and confirmed printability of one of them on a MII tool.

  17. FPT Algorithm for Two-Dimensional Cyclic Convolutions

    NASA Technical Reports Server (NTRS)

    Truong, Trieu-Kie; Shao, Howard M.; Pei, D. Y.; Reed, Irving S.

    1987-01-01

    Fast-polynomial-transform (FPT) algorithm computes two-dimensional cyclic convolution of two-dimensional arrays of complex numbers. New algorithm uses cyclic polynomial convolutions of same length. Algorithm regular, modular, and expandable.

  18. Mechanisms of circumferential gyral convolution in primate brains.

    PubMed

    Zhang, Tuo; Razavi, Mir Jalil; Chen, Hanbo; Li, Yujie; Li, Xiao; Li, Longchuan; Guo, Lei; Hu, Xiaoping; Liu, Tianming; Wang, Xianqiao

    2017-06-01

    Mammalian cerebral cortices are characterized by elaborate convolutions. Radial convolutions exhibit homology across primate species and generally are easily identified in individuals of the same species. In contrast, circumferential convolutions vary across species as well as individuals of the same species. However, systematic study of circumferential convolution patterns is lacking. To address this issue, we utilized structural MRI (sMRI) and diffusion MRI (dMRI) data from primate brains. We quantified cortical thickness and circumferential convolutions on gyral banks in relation to axonal pathways and density along the gray matter/white matter boundaries. Based on these observations, we performed a series of computational simulations. Results demonstrated that the interplay of heterogeneous cortex growth and mechanical forces along axons plays a vital role in the regulation of circumferential convolutions. In contrast, gyral geometry controls the complexity of circumferential convolutions. These findings offer insight into the mystery of circumferential convolutions in primate brains.

  19. Investigation of dosimetric differences between the TMR 10 and convolution algorithm for Gamma Knife stereotactic radiosurgery.

    PubMed

    Rojas-Villabona, Alvaro; Kitchen, Neil; Paddick, Ian

    2016-11-01

    , but consistent, dose shift compared to the TMR 10 algorithm traditionally used for GKR. A reduction of the prescription dose may be necessary to obtain the same clinical effect with the convolution algorithm. Head shape definition using CT outlining can reduce treatment uncertainty from head shape approximations. PACS number(s): 87.53.-j; 87.55.D; 87.55.kd. © 2016 The Authors.

  20. Investigation of dosimetric differences between the TMR 10 and convolution algorithm for Gamma Knife stereotactic radiosurgery.

    PubMed

    Rojas-Villabona, Alvaro; Kitchen, Neil; Paddick, Ian

    2016-11-08

    considerable, but consistent, dose shift compared to the TMR 10 algorithm traditionally used for GKR. A reduction of the prescription dose may be neces-sary to obtain the same clinical effect with the convolution algorithm. Head shape definition using CT outlining can reduce treatment uncertainty from head shape approximations. © 2016 The Authors.

  1. Multiple deep convolutional neural networks averaging for face alignment

    NASA Astrophysics Data System (ADS)

    Zhang, Shaohua; Yang, Hua; Yin, Zhouping

    2015-05-01

    Face alignment is critical for face recognition, and the deep learning-based method shows promise for solving such issues, given that competitive results are achieved on benchmarks with additional benefits, such as dispensing with handcrafted features and initial shape. However, most existing deep learning-based approaches are complicated and quite time-consuming during training. We propose a compact face alignment method for fast training without decreasing its accuracy. Rectified linear unit is employed, which allows all networks approximately five times faster convergence than a tanh neuron. An eight learnable layer deep convolutional neural network (DCNN) based on local response normalization and a padding convolutional layer (PCL) is designed to provide reliable initial values during prediction. A model combination scheme is presented to further reduce errors, while showing that only two network architectures and hyperparameter selection procedures are required in our approach. A three-level cascaded system is ultimately built based on the DCNNs and model combination mode. Extensive experiments validate the effectiveness of our method and demonstrate comparable accuracy with state-of-the-art methods on BioID, labeled face parts in the wild, and Helen datasets.

  2. Flexible Fabrication of Shape-Controlled Collagen Building Blocks for Self-Assembly of 3D Microtissues.

    PubMed

    Zhang, Xu; Meng, Zhaoxu; Ma, Jingyun; Shi, Yang; Xu, Hui; Lykkemark, Simon; Qin, Jianhua

    2015-08-12

    Creating artificial tissue-like structures that possess the functionality, specificity, and architecture of native tissues remains a big challenge. A new and straightforward strategy for generating shape-controlled collagen building blocks with a well-defined architecture is presented, which can be used for self-assembly of complex 3D microtissues. Collagen blocks with tunable geometries are controllably produced and released via a membrane-templated microdevice. The formation of functional microtissues by embedding tissue-specific cells into collagen blocks with expression of specific proteins is described. The spontaneous self-assembly of cell-laden collagen blocks into organized tissue constructs with predetermined configurations is demonstrated, which are largely driven by the synergistic effects of cell-cell and cell-matrix interactions. This new strategy would open up new avenues for the study of tissue/organ morphogenesis, and tissue engineering applications.

  3. Fused Deposition Modeling Enables the Low-Cost Fabrication of Porous, Customized-Shape Sorbents for Small-Molecule Extraction.

    PubMed

    Belka, Mariusz; Ulenberg, Szymon; Bączek, Tomasz

    2017-04-07

    Fused deposition modeling, one of the most common techniques in three-dimensional printing and additive manufacturing, has many practical applications in the fields of chemistry and pharmacy. We demonstrate that a thermoplastic elastomer-poly(vinyl alcohol) (PVA) composite material (LAY-FOMM 60), which presents porous properties after PVA removal, is useful for the extraction of small-molecule drug-like compounds from water samples. The usefulness of the proposed approach is demonstrated by the extraction of glimepiride from a water sample, followed by LC-MS analysis. The recovery was 82.24%, with a relative standard deviation of less than 5%. The proposed approach can change the way of thinking about extraction and sample preparation due to a shift to the use of sorbents with customizable size, shape, and chemical properties that do not rely on commercial suppliers.

  4. Towards dropout training for convolutional neural networks.

    PubMed

    Wu, Haibing; Gu, Xiaodong

    2015-11-01

    Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Sequential Syndrome Decoding of Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1984-01-01

    The algebraic structure of convolutional codes are reviewed and sequential syndrome decoding is applied to those codes. These concepts are then used to realize by example actual sequential decoding, using the stack algorithm. The Fano metric for use in sequential decoding is modified so that it can be utilized to sequentially find the minimum weight error sequence.

  6. Number-Theoretic Functions via Convolution Rings.

    ERIC Educational Resources Information Center

    Berberian, S. K.

    1992-01-01

    Demonstrates the number theory property that the number of divisors of an integer n times the number of positive integers k, less than or equal to and relatively prime to n, equals the sum of the divisors of n using theory developed about multiplicative functions, the units of a convolution ring, and the Mobius Function. (MDH)

  7. Convolutions and Their Applications in Information Science.

    ERIC Educational Resources Information Center

    Rousseau, Ronald

    1998-01-01

    Presents definitions of convolutions, mathematical operations between sequences or between functions, and gives examples of their use in information science. In particular they can be used to explain the decline in the use of older literature (obsolescence) or the influence of publication delays on the aging of scientific literature. (Author/LRW)

  8. VLSI Unit for Two-Dimensional Convolutions

    NASA Technical Reports Server (NTRS)

    Liu, K. Y.

    1983-01-01

    Universal logic structure allows same VLSI chip to be used for variety of computational functions required for two dimensional convolutions. Fast polynomial transform technique is extended into tree computational structure composed of two units: fast polynomial transform (FPT) unit and Chinese remainder theorem (CRT) computational unit.

  9. A fluence-convolution method to calculate radiation therapy dose distributions that incorporate random set-up error

    NASA Astrophysics Data System (ADS)

    Beckham, W. A.; Keall, P. J.; Siebers, J. V.

    2002-10-01

    The International Commission on Radiation Units and Measurements Report 62 (ICRU 1999) introduced the concept of expanding the clinical target volume (CTV) to form the planning target volume by a two-step process. The first step is adding a clinically definable internal margin, which produces an internal target volume that accounts for the size, shape and position of the CTV in relation to anatomical reference points. The second is the use of a set-up margin (SM) that incorporates the uncertainties of patient beam positioning, i.e. systematic and random set-up errors. We propose to replace the random set-up error component of the SM by explicitly incorporating the random set-up error into the dose-calculation model by convolving the incident photon beam fluence with a Gaussian set-up error kernel. This fluence-convolution method was implemented into a Monte Carlo (MC) based treatment-planning system. Also implemented for comparison purposes was a dose-matrix-convolution algorithm similar to that described by Leong (1987 Phys. Med. Biol. 32 327-34). Fluence and dose-matrix-convolution agree in homogeneous media. However, for the heterogeneous phantom calculations, discrepancies of up to 5% in the dose profiles were observed with a 0.4 cm set-up error value. Fluence-convolution mimics reality more closely, as dose perturbations at interfaces are correctly predicted (Wang et al 1999 Med. Phys. 26 2626-34, Sauer 1995 Med. Phys. 22 1685-90). Fluence-convolution effectively decouples the treatment beams from the patient, and more closely resembles the reality of particle fluence distributions for many individual beam-patient set-ups. However, dose-matrix-convolution reduces the random statistical noise in MC calculations. Fluence-convolution can easily be applied to convolution/superposition based dose-calculation algorithms.

  10. Convolution theorems: partitioning the space of integral transforms

    NASA Astrophysics Data System (ADS)

    Lindsey, Alan R.; Suter, Bruce W.

    1999-03-01

    Investigating a number of different integral transforms uncovers distinct patterns in the type of translation convolution theorems afforded by each. It is shown that transforms based on separable kernels (aka Fourier, Laplace and their relatives) have a form of the convolution theorem providing for a transform domain product of the convolved functions. However, transforms based on kernels not separable in the function and transform variables mandate a convolution theorem of a different type; namely in the transform domain the convolution becomes another convolution--one function with the transform of the other.

  11. Effectiveness of Convolutional Code in Multipath Underwater Acoustic Channel

    NASA Astrophysics Data System (ADS)

    Park, Jihyun; Seo, Chulwon; Park, Kyu-Chil; Yoon, Jong Rak

    2013-07-01

    The forward error correction (FEC) is achieved by increasing redundancy of information. Convolutional coding with Viterbi decoding is a typical FEC technique in channel corrupted by additive white gaussian noise. But the FEC effectiveness of convolutional code is questioned in multipath frequency selective fading channel. In this paper, how convolutional code works in multipath channel in underwater, is examined. Bit error rates (BER) with and without 1/2 convolutional code are analyzed based on channel bandwidth which is frequency selectivity parameter. It is found that convolution code performance is well matched in non selective channel and also effective in selective channel.

  12. (Ti, O)/Ti and (Ti, O, N)/Ti composite coatings fabricated via PIIID for the medical application of NiTi shape memory alloy.

    PubMed

    Sun, Tao; Wang, Lang-Ping; Wang, Min

    2011-02-01

    In this investigation, the plasma immersion ion implantation and deposition (PIIID) technique was used to fabricate (Ti, O)/Ti or (Ti, O, N)/Ti coatings on a NiTi shape memory alloy (SMA, 50.8 at.% Ni) to improve its corrosion, wear resistance, and bioactivity. After coating fabrication, the structure and properties of composite coatings were studied, and the coated and uncoated NiTi SMA samples were compared with each other. Scanning electron microscopic (SEM) examination of coating surfaces and cross-sections showed that (Ti, O)/Ti and (Ti, O, N)/Ti composite coatings were dense and uniform, having thickness values of 1.16 ± 0.08 μm and 0.95 ± 0.06 μm, respectively. X-ray diffraction (XRD) results revealed that there were no diffraction peaks corresponding to TiO(2) or TiN for (Ti, O)/Ti and (Ti, O, N)/Ti composite coatings, suggesting that after the PIIID treatment, TiO(2) and TiN were amorphous or nanosized in the coatings. Energy dispersive X-ray (EDX) analysis indicated that the interface between the coating and NiTi SMA substrate was gradual rather than sharp. In addition, EDX elemental mapping of coating cross-sections showed that Ni was depleted from the surface. Differential scanning calorimetry (DSC) curves revealed that the shape memory ability of NiTi SMA was not degraded by the PIIID treatment. The width of wear tracks on (Ti, O, N)/Ti coated NiTi SMA samples was reduced 6.5-fold, in comparison with that on uncoated samples. The corrosion potential (E(corr) ) was improved from -466.20 ± 37.82 mV for uncoated samples to 125.50 ± 21.49 mV and -185.40 ± 37.05 mV for (Ti, O)/Ti coated and (Ti, O, N)/Ti coated samples, respectively. Both types of coatings facilitated bone-like apatite formation on the surface of NiTi SMA in simulated body fluid (SBF), indicating their in vitro bioactivity.

  13. A convolutional neural network neutrino event classifier

    NASA Astrophysics Data System (ADS)

    Aurisano, A.; Radovic, A.; Rocco, D.; Himmel, A.; Messier, M. D.; Niner, E.; Pawloski, G.; Psihas, F.; Sousa, A.; Vahle, P.

    2016-09-01

    Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  14. DCMDN: Deep Convolutional Mixture Density Network

    NASA Astrophysics Data System (ADS)

    D'Isanto, Antonio; Polsterer, Kai Lars

    2017-09-01

    Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

  15. A Construction of MDS Quantum Convolutional Codes

    NASA Astrophysics Data System (ADS)

    Zhang, Guanghui; Chen, Bocong; Li, Liangchen

    2015-09-01

    In this paper, two new families of MDS quantum convolutional codes are constructed. The first one can be regarded as a generalization of [36, Theorem 6.5], in the sense that we do not assume that q≡1 (mod 4). More specifically, we obtain two classes of MDS quantum convolutional codes with parameters: (i) [( q 2+1, q 2-4 i+3,1;2,2 i+2)] q , where q≥5 is an odd prime power and 2≤ i≤( q-1)/2; (ii) , where q is an odd prime power with the form q=10 m+3 or 10 m+7 ( m≥2), and 2≤ i≤2 m-1.

  16. Deep Learning with Hierarchical Convolutional Factor Analysis

    PubMed Central

    Chen, Bo; Polatkan, Gungor; Sapiro, Guillermo; Blei, David; Dunson, David; Carin, Lawrence

    2013-01-01

    Unsupervised multi-layered (“deep”) models are considered for general data, with a particular focus on imagery. The model is represented using a hierarchical convolutional factor-analysis construction, with sparse factor loadings and scores. The computation of layer-dependent model parameters is implemented within a Bayesian setting, employing a Gibbs sampler and variational Bayesian (VB) analysis, that explicitly exploit the convolutional nature of the expansion. In order to address large-scale and streaming data, an online version of VB is also developed. The number of basis functions or dictionary elements at each layer is inferred from the data, based on a beta-Bernoulli implementation of the Indian buffet process. Example results are presented for several image-processing applications, with comparisons to related models in the literature. PMID:23787342

  17. Performance of convolutionally coded unbalanced QPSK systems

    NASA Technical Reports Server (NTRS)

    Divsalar, D.; Yuen, J. H.

    1980-01-01

    An evaluation is presented of the performance of three representative convolutionally coded unbalanced quadri-phase-shift-keying (UQPSK) systems in the presence of noisy carrier reference and crosstalk. The use of a coded UQPSK system for transmitting two telemetry data streams with different rates and different powers has been proposed for the Venus Orbiting Imaging Radar mission. Analytical expressions for bit error rates in the presence of a noisy carrier phase reference are derived for three representative cases: (1) I and Q channels are coded independently; (2) I channel is coded, Q channel is uncoded; and (3) I and Q channels are coded by a common 1/2 code. For rate 1/2 convolutional codes, QPSK modulation can be used to reduce the bandwidth requirement.

  18. Digital Correlation By Optical Convolution/Correlation

    NASA Astrophysics Data System (ADS)

    Trimble, Joel; Casasent, David; Psaltis, Demetri; Caimi, Frank; Carlotto, Mark; Neft, Deborah

    1980-12-01

    Attention is given to various methods by which the accuracy achieveable and the dynamic range requirements of an optical computer can be enhanced. A new time position coding acousto-optic technique for optical residue arithmetic processing is presented and experimental demonstration is included. Major attention is given to the implementation of a correlator operating on digital or decimal encoded signals. Using a convolution description of multiplication, we realize such a correlator by optical convolution in one dimension and optical correlation in the other dimension of a optical system. A coherent matched spatial filter system operating on digital encoded signals, a noncoherent processor operating on complex-valued digital-encoded data, and a real-time multi-channel acousto-optic system for such operations are described and experimental verifications are included.

  19. A convolutional neural network neutrino event classifier

    DOE PAGES

    Aurisano, A.; Radovic, A.; Rocco, D.; ...

    2016-09-01

    Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

  20. A convolutional neural network neutrino event classifier

    SciTech Connect

    Aurisano, A.; Radovic, A.; Rocco, D.; Himmel, A.; Messier, M. D.; Niner, E.; Pawloski, G.; Psihas, F.; Sousa, A.; Vahle, P.

    2016-09-01

    Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  1. A convolutional neural network neutrino event classifier

    SciTech Connect

    Aurisano, A.; Radovic, A.; Rocco, D.; Himmel, A.; Messier, M. D.; Niner, E.; Pawloski, G.; Psihas, F.; Sousa, A.; Vahle, P.

    2016-09-01

    Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  2. Quantum convolutional codes derived from constacyclic codes

    NASA Astrophysics Data System (ADS)

    Yan, Tingsu; Huang, Xinmei; Tang, Yuansheng

    2014-12-01

    In this paper, three families of quantum convolutional codes are constructed. The first one and the second one can be regarded as a generalization of Theorems 3, 4, 7 and 8 [J. Chen, J. Li, F. Yang and Y. Huang, Int. J. Theor. Phys., doi:10.1007/s10773-014-2214-6 (2014)], in the sense that we drop the constraint q ≡ 1 (mod 4). Furthermore, the second one and the third one attain the quantum generalized Singleton bound.

  3. Long decoding runs for Galileo's convolutional codes

    NASA Technical Reports Server (NTRS)

    Lahmeyer, C. R.; Cheung, K.-M.

    1988-01-01

    Decoding results are described for long decoding runs of Galileo's convolutional codes. A 1 k-bit/sec hardware Viterbi decoder is used for the (15, 1/4) convolutional code, and a software Viterbi decoder is used for the (7, 1/2) convolutional code. The output data of these long runs are stored in data files using a data compression format which can reduce file size by a factor of 100 to 1 typically. These data files can be used to replicate the long, time-consuming runs exactly and are useful to anyone who wants to analyze the burst statistics of the Viterbi decoders. The 1 k-bit/sec hardware Viterbi decoder was developed in order to demonstrate the correctness of certain algorithmic concepts for decoding Galileo's experimental (15, 1/4) code, and for the long-constraint-length codes in general. The hardware decoder can be used both to search for good codes and to measure accurately the performance of known codes.

  4. A novel one-pot process for near-net-shape fabrication of open-porous resorbable hydroxyapatite/protein composites and in vivo assessment.

    PubMed

    Mueller, Berit; Koch, Dietmar; Lutz, Rainer; Schlegel, Karl A; Treccani, Laura; Rezwan, Kurosch

    2014-09-01

    We present a mild one-pot freeze gelation process for fabricating near-net, complex-shaped hydroxyapatite scaffolds and to directly incorporate active proteins during scaffold processing. In particular, the direct protein incorporation enables a simultaneous adjustment and control of scaffold microstructure, porosity, resorbability and enhancement of initial mechanical and handling stability. Two proteins, serum albumin and lysozyme, are selected and their effect on scaffold stability and microstructure investigated by biaxial strength tests, electron microscopy, and mercury intrusion porosimetry. The resulting hydroxyapatite/protein composites feature adjustable porosities from 50% to 70% and a mechanical strength ranging from 2 to 6 MPa comparable to that of human spongiosa without any sintering step. Scaffold degradation behaviour and protein release are assessed by in vitro studies. A preliminary in vivo assessment of scaffold biocompatibility and resorption behaviour in adult domestic pigs is discussed. After implantation, composites were resorbed up to 50% after only 4 weeks and up to 65% after 8 weeks. In addition, 14% new bone formation after 4 weeks and 37% after 8 weeks were detected. All these investigations demonstrate the outstanding suitability of the one-pot-process to create, in a customisable and reliable way, biocompatible scaffolds with sufficient mechanical strength for handling and surgical insertion, and for potential use as biodegradable bone substitutes and versatile platform for local drug delivery.

  5. Space reactor shielding fabrication

    NASA Technical Reports Server (NTRS)

    Welch, F. H.

    1972-01-01

    The fabrication of space reactor neutron shielding by a melting and casting process utilizing lithium hydride is described. The first neutron shield fabricated is a large pancake shape 86 inches in diameter, containing about 1700 pounds of lithium hydride. This shield, fabricated by the unique melting and casting process, is the largest lithium hydride shield ever built.

  6. The analysis of convolutional codes via the extended Smith algorithm

    NASA Technical Reports Server (NTRS)

    Mceliece, R. J.; Onyszchuk, I.

    1993-01-01

    Convolutional codes have been the central part of most error-control systems in deep-space communication for many years. Almost all such applications, however, have used the restricted class of (n,1), also known as 'rate 1/n,' convolutional codes. The more general class of (n,k) convolutional codes contains many potentially useful codes, but their algebraic theory is difficult and has proved to be a stumbling block in the evolution of convolutional coding systems. In this article, the situation is improved by describing a set of practical algorithms for computing certain basic things about a convolutional code (among them the degree, the Forney indices, a minimal generator matrix, and a parity-check matrix), which are usually needed before a system using the code can be built. The approach is based on the classic Forney theory for convolutional codes, together with the extended Smith algorithm for polynomial matrices, which is introduced in this article.

  7. A fast complex integer convolution using a hybrid transform

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; K Truong, T.

    1978-01-01

    It is shown that the Winograd transform can be combined with a complex integer transform over the Galois field GF(q-squared) to yield a new algorithm for computing the discrete cyclic convolution of complex number points. By this means a fast method for accurately computing the cyclic convolution of a sequence of complex numbers for long convolution lengths can be obtained. This new hybrid algorithm requires fewer multiplications than previous algorithms.

  8. Convolutional Architecture Exploration for Action Recognition and Image Classification

    DTIC Science & Technology

    2015-01-01

    Convolutional Architecture Exploration for Action Recognition and Image Classification JT Turner∗1, David Aha2, Leslie Smith2, and Kalyan Moy Gupta1...Intelligence; Naval Research Laboratory (Code 5514); Washington, DC 20375 Abstract Convolutional Architecture for Fast Feature Encoding (CAFFE) [11] is a soft...This is especially true with convolutional neural networks which depend upon the architecture to detect edges and objects in the same way the human

  9. A fast complex integer convolution using a hybrid transform

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; K Truong, T.

    1978-01-01

    It is shown that the Winograd transform can be combined with a complex integer transform over the Galois field GF(q-squared) to yield a new algorithm for computing the discrete cyclic convolution of complex number points. By this means a fast method for accurately computing the cyclic convolution of a sequence of complex numbers for long convolution lengths can be obtained. This new hybrid algorithm requires fewer multiplications than previous algorithms.

  10. SU-E-T-08: A Convolution Model for Head Scatter Fluence in the Intensity Modulated Field

    SciTech Connect

    Chen, M; Mo, X; Chen, Y; Parnell, D; Key, S; Olivera, G; Galmarini, W; Lu, W

    2014-06-01

    Purpose: To efficiently calculate the head scatter fluence for an arbitrary intensity-modulated field with any source distribution using the source occlusion model. Method: The source occlusion model with focal and extra focal radiation (Jaffray et al, 1993) can be used to account for LINAC head scatter. In the model, the fluence map of any field shape at any point can be calculated via integration of the source distribution within the visible range, as confined by each segment, using the detector eye's view. A 2D integration would be required for each segment and each fluence plane point, which is time-consuming, as an intensity-modulated field contains typically tens to hundreds of segments. In this work, we prove that the superposition of the segmental integrations is equivalent to a simple convolution regardless of what the source distribution is. In fact, for each point, the detector eye's view of the field shape can be represented as a function with the origin defined at the point's pinhole reflection through the center of the collimator plane. We were thus able to reduce hundreds of source plane integration to one convolution. We calculated the fluence map for various 3D and IMRT beams and various extra-focal source distributions using both the segmental integration approach and the convolution approach and compared the computation time and fluence map results of both approaches. Results: The fluence maps calculated using the convolution approach were the same as those calculated using the segmental approach, except for rounding errors (<0.1%). While it took considerably longer time to calculate all segmental integrations, the fluence map calculation using the convolution approach took only ∼1/3 of the time for typical IMRT fields with ∼100 segments. Conclusions: The convolution approach for head scatter fluence calculation is fast and accurate and can be used to enhance the online process.

  11. Human Parsing with Contextualized Convolutional Neural Network.

    PubMed

    Liang, Xiaodan; Xu, Chunyan; Shen, Xiaohui; Yang, Jianchao; Tang, Jinhui; Lin, Liang; Yan, Shuicheng

    2016-03-02

    In this work, we address the human parsing task with a novel Contextualized Convolutional Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global image-level context, semantic edge context, within-super-pixel context and cross-super-pixel neighborhood context into a unified network. Given an input human image, Co-CNN produces the pixel-wise categorization in an end-to-end way. First, the cross-layer context is captured by our basic local-to-global-to-local structure, which hierarchically combines the global semantic information and the local fine details across different convolutional layers. Second, the global image-level label prediction is used as an auxiliary objective in the intermediate layer of the Co-CNN, and its outputs are further used for guiding the feature learning in subsequent convolutional layers to leverage the global imagelevel context. Third, semantic edge context is further incorporated into Co-CNN, where the high-level semantic boundaries are leveraged to guide pixel-wise labeling. Finally, to further utilize the local super-pixel contexts, the within-super-pixel smoothing and cross-super-pixel neighbourhood voting are formulated as natural sub-components of the Co-CNN to achieve the local label consistency in both training and testing process. Comprehensive evaluations on two public datasets well demonstrate the significant superiority of our Co-CNN over other state-of-the-arts for human parsing. In particular, the F-1 score on the large dataset [1] reaches 81:72% by Co-CNN, significantly higher than 62:81% and 64:38% by the state-of-the-art algorithms, MCNN [2] and ATR [1], respectively. By utilizing our newly collected large dataset for training, our Co-CNN can achieve 85:36% in F-1 score.

  12. Applications of convolution voltammetry in electroanalytical chemistry.

    PubMed

    Bentley, Cameron L; Bond, Alan M; Hollenkamp, Anthony F; Mahon, Peter J; Zhang, Jie

    2014-02-18

    The robustness of convolution voltammetry for determining accurate values of the diffusivity (D), bulk concentration (C(b)), and stoichiometric number of electrons (n) has been demonstrated by applying the technique to a series of electrode reactions in molecular solvents and room temperature ionic liquids (RTILs). In acetonitrile, the relatively minor contribution of nonfaradaic current facilitates analysis with macrodisk electrodes, thus moderate scan rates can be used without the need to perform background subtraction to quantify the diffusivity of iodide [D = 1.75 (±0.02) × 10(-5) cm(2) s(-1)] in this solvent. In the RTIL 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide, background subtraction is necessary at a macrodisk electrode but can be avoided at a microdisk electrode, thereby simplifying the analytical procedure and allowing the diffusivity of iodide [D = 2.70 (±0.03) × 10(-7) cm(2) s(-1)] to be quantified. Use of a convolutive procedure which simultaneously allows D and nC(b) values to be determined is also demonstrated. Three conditions under which a technique of this kind may be applied are explored and are related to electroactive species which display slow dissolution kinetics, undergo a single multielectron transfer step, or contain multiple noninteracting redox centers using ferrocene in an RTIL, 1,4-dinitro-2,3,5,6-tetramethylbenzene, and an alkynylruthenium trimer, respectively, as examples. The results highlight the advantages of convolution voltammetry over steady-state techniques such as rotating disk electrode voltammetry and microdisk electrode voltammetry, as it is not restricted by the mode of diffusion (planar or radial), hence removing limitations on solvent viscosity, electrode geometry, and voltammetric scan rate.

  13. Zebrafish tracking using convolutional neural networks

    PubMed Central

    XU, Zhiping; Cheng, Xi En

    2017-01-01

    Keeping identity for a long term after occlusion is still an open problem in the video tracking of zebrafish-like model animals, and accurate animal trajectories are the foundation of behaviour analysis. We utilize the highly accurate object recognition capability of a convolutional neural network (CNN) to distinguish fish of the same congener, even though these animals are indistinguishable to the human eye. We used data augmentation and an iterative CNN training method to optimize the accuracy for our classification task, achieving surprisingly accurate trajectories of zebrafish of different size and age zebrafish groups over different time spans. This work will make further behaviour analysis more reliable. PMID:28211462

  14. Zebrafish tracking using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Xu, Zhiping; Cheng, Xi En

    2017-02-01

    Keeping identity for a long term after occlusion is still an open problem in the video tracking of zebrafish-like model animals, and accurate animal trajectories are the foundation of behaviour analysis. We utilize the highly accurate object recognition capability of a convolutional neural network (CNN) to distinguish fish of the same congener, even though these animals are indistinguishable to the human eye. We used data augmentation and an iterative CNN training method to optimize the accuracy for our classification task, achieving surprisingly accurate trajectories of zebrafish of different size and age zebrafish groups over different time spans. This work will make further behaviour analysis more reliable.

  15. Convolutional coding combined with continuous phase modulation

    NASA Technical Reports Server (NTRS)

    Pizzi, S. V.; Wilson, S. G.

    1985-01-01

    Background theory and specific coding designs for combined coding/modulation schemes utilizing convolutional codes and continuous-phase modulation (CPM) are presented. In this paper the case of r = 1/2 coding onto a 4-ary CPM is emphasized, with short-constraint length codes presented for continuous-phase FSK, double-raised-cosine, and triple-raised-cosine modulation. Coding buys several decibels of coding gain over the Gaussian channel, with an attendant increase of bandwidth. Performance comparisons in the power-bandwidth tradeoff with other approaches are made.

  16. QCDNUM: Fast QCD evolution and convolution

    NASA Astrophysics Data System (ADS)

    Botje, M.

    2011-02-01

    The QCDNUM program numerically solves the evolution equations for parton densities and fragmentation functions in perturbative QCD. Un-polarised parton densities can be evolved up to next-to-next-to-leading order in powers of the strong coupling constant, while polarised densities or fragmentation functions can be evolved up to next-to-leading order. Other types of evolution can be accessed by feeding alternative sets of evolution kernels into the program. A versatile convolution engine provides tools to compute parton luminosities, cross-sections in hadron-hadron scattering, and deep inelastic structure functions in the zero-mass scheme or in generalised mass schemes. Input to these calculations are either the QCDNUM evolved densities, or those read in from an external parton density repository. Included in the software distribution are packages to calculate zero-mass structure functions in un-polarised deep inelastic scattering, and heavy flavour contributions to these structure functions in the fixed flavour number scheme. Program summaryProgram title: QCDNUM version: 17.00 Catalogue identifier: AEHV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Public Licence No. of lines in distributed program, including test data, etc.: 45 736 No. of bytes in distributed program, including test data, etc.: 911 569 Distribution format: tar.gz Programming language: Fortran-77 Computer: All Operating system: All RAM: Typically 3 Mbytes Classification: 11.5 Nature of problem: Evolution of the strong coupling constant and parton densities, up to next-to-next-to-leading order in perturbative QCD. Computation of observable quantities by Mellin convolution of the evolved densities with partonic cross-sections. Solution method: Parametrisation of the parton densities as linear or quadratic splines on a discrete grid, and evolution of the spline

  17. Fast Convolution Algorithms and Associated VHSIC Architectures.

    DTIC Science & Technology

    1983-05-23

    Idenftfy by block number) Finite field, Mersenne prime , Fermat number, primitive element, number- theoretic transform, cyclic convolution, polynomial...elements of order 2 P+p and 2k n in the finite field GF(q 2), where q = 2P-l is a Mersenne prime , p is a prime number, and n is a divisor of 2pl...Abstract - A high-radix f.f.t. algorithm for computing transforms over GF(q2), where q is a Mersenne prime , is developed to implement fast circular

  18. Bacterial colony counting by Convolutional Neural Networks.

    PubMed

    Ferrari, Alessandro; Lombardi, Stefano; Signoroni, Alberto

    2015-01-01

    Counting bacterial colonies on microbiological culture plates is a time-consuming, error-prone, nevertheless fundamental task in microbiology. Computer vision based approaches can increase the efficiency and the reliability of the process, but accurate counting is challenging, due to the high degree of variability of agglomerated colonies. In this paper, we propose a solution which adopts Convolutional Neural Networks (CNN) for counting the number of colonies contained in confluent agglomerates, that scored an overall accuracy of the 92.8% on a large challenging dataset. The proposed CNN-based technique for estimating the cardinality of colony aggregates outperforms traditional image processing approaches, becoming a promising approach to many related applications.

  19. Convolutional coding combined with continuous phase modulation

    NASA Technical Reports Server (NTRS)

    Pizzi, S. V.; Wilson, S. G.

    1985-01-01

    Background theory and specific coding designs for combined coding/modulation schemes utilizing convolutional codes and continuous-phase modulation (CPM) are presented. In this paper the case of r = 1/2 coding onto a 4-ary CPM is emphasized, with short-constraint length codes presented for continuous-phase FSK, double-raised-cosine, and triple-raised-cosine modulation. Coding buys several decibels of coding gain over the Gaussian channel, with an attendant increase of bandwidth. Performance comparisons in the power-bandwidth tradeoff with other approaches are made.

  20. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

    PubMed

    Chen, Liang-Chieh; Papandreou, George; Kokkinos, Iasonas; Murphy, Kevin; Yuille, Alan L

    2017-04-27

    In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second, we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third, we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7% mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.

  1. Convolutional fountain distribution over fading wireless channels

    NASA Astrophysics Data System (ADS)

    Usman, Mohammed

    2012-08-01

    Mobile broadband has opened the possibility of a rich variety of services to end users. Broadcast/multicast of multimedia data is one such service which can be used to deliver multimedia to multiple users economically. However, the radio channel poses serious challenges due to its time-varying properties, resulting in each user experiencing different channel characteristics, independent of other users. Conventional methods of achieving reliability in communication, such as automatic repeat request and forward error correction do not scale well in a broadcast/multicast scenario over radio channels. Fountain codes, being rateless and information additive, overcome these problems. Although the design of fountain codes makes it possible to generate an infinite sequence of encoded symbols, the erroneous nature of radio channels mandates the need for protecting the fountain-encoded symbols, so that the transmission is feasible. In this article, the performance of fountain codes in combination with convolutional codes, when used over radio channels, is presented. An investigation of various parameters, such as goodput, delay and buffer size requirements, pertaining to the performance of fountain codes in a multimedia broadcast/multicast environment is presented. Finally, a strategy for the use of 'convolutional fountain' over radio channels is also presented.

  2. Convolution formulations for non-negative intensity.

    PubMed

    Williams, Earl G

    2013-08-01

    Previously unknown spatial convolution formulas for a variant of the active normal intensity in planar coordinates have been derived that use measured pressure or normal velocity near-field holograms to construct a positive-only (outward) intensity distribution in the plane, quantifying the areas of the vibrating structure that produce radiation to the far-field. This is an extension of the outgoing-only (unipolar) intensity technique recently developed for arbitrary geometries by Steffen Marburg. The method is applied independently to pressure and velocity data measured in a plane close to the surface of a point-driven, unbaffled rectangular plate in the laboratory. It is demonstrated that the sound producing regions of the structure are clearly revealed using the derived formulas and that the spatial resolution is limited to a half-wavelength. A second set of formulas called the hybrid-intensity formulas are also derived which yield a bipolar intensity using a different spatial convolution operator, again using either the measured pressure or velocity. It is demonstrated from the experiment results that the velocity formula yields the classical active intensity and the pressure formula an interesting hybrid intensity that may be useful for source localization. Computations are fast and carried out in real space without Fourier transforms into wavenumber space.

  3. NUCLEI SEGMENTATION VIA SPARSITY CONSTRAINED CONVOLUTIONAL REGRESSION

    PubMed Central

    Zhou, Yin; Chang, Hang; Barner, Kenneth E.; Parvin, Bahram

    2017-01-01

    Automated profiling of nuclear architecture, in histology sections, can potentially help predict the clinical outcomes. However, the task is challenging as a result of nuclear pleomorphism and cellular states (e.g., cell fate, cell cycle), which are compounded by the batch effect (e.g., variations in fixation and staining). Present methods, for nuclear segmentation, are based on human-designed features that may not effectively capture intrinsic nuclear architecture. In this paper, we propose a novel approach, called sparsity constrained convolutional regression (SCCR), for nuclei segmentation. Specifically, given raw image patches and the corresponding annotated binary masks, our algorithm jointly learns a bank of convolutional filters and a sparse linear regressor, where the former is used for feature extraction, and the latter aims to produce a likelihood for each pixel being nuclear region or background. During classification, the pixel label is simply determined by a thresholding operation applied on the likelihood map. The method has been evaluated using the benchmark dataset collected from The Cancer Genome Atlas (TCGA). Experimental results demonstrate that our method outperforms traditional nuclei segmentation algorithms and is able to achieve competitive performance compared to the state-of-the-art algorithm built upon human-designed features with biological prior knowledge. PMID:28101301

  4. Convolution Inequalities for the Boltzmann Collision Operator

    NASA Astrophysics Data System (ADS)

    Alonso, Ricardo J.; Carneiro, Emanuel; Gamba, Irene M.

    2010-09-01

    We study integrability properties of a general version of the Boltzmann collision operator for hard and soft potentials in n-dimensions. A reformulation of the collisional integrals allows us to write the weak form of the collision operator as a weighted convolution, where the weight is given by an operator invariant under rotations. Using a symmetrization technique in L p we prove a Young’s inequality for hard potentials, which is sharp for Maxwell molecules in the L 2 case. Further, we find a new Hardy-Littlewood-Sobolev type of inequality for Boltzmann collision integrals with soft potentials. The same method extends to radially symmetric, non-increasing potentials that lie in some {Ls_{weak}} or L s . The method we use resembles a Brascamp, Lieb and Luttinger approach for multilinear weighted convolution inequalities and follows a weak formulation setting. Consequently, it is closely connected to the classical analysis of Young and Hardy-Littlewood-Sobolev inequalities. In all cases, the inequality constants are explicitly given by formulas depending on integrability conditions of the angular cross section (in the spirit of Grad cut-off). As an additional application of the technique we also obtain estimates with exponential weights for hard potentials in both conservative and dissipative interactions.

  5. New quantum MDS-convolutional codes derived from constacyclic codes

    NASA Astrophysics Data System (ADS)

    Li, Fengwei; Yue, Qin

    2015-12-01

    In this paper, we utilize a family of Hermitian dual-containing constacyclic codes to construct classical and quantum MDS convolutional codes. Our classical and quantum convolutional codes are optimal in the sense that they attain the classical (quantum) generalized Singleton bound.

  6. Experimental Investigation of Convoluted Contouring for Aircraft Afterbody Drag Reduction

    NASA Technical Reports Server (NTRS)

    Deere, Karen A.; Hunter, Craig A.

    1999-01-01

    An experimental investigation was performed in the NASA Langley 16-Foot Transonic Tunnel to determine the aerodynamic effects of external convolutions, placed on the boattail of a nonaxisymmetric nozzle for drag reduction. Boattail angles of 15 and 22 were tested with convolutions placed at a forward location upstream of the boattail curvature, at a mid location along the curvature and at a full location that spanned the entire boattail flap. Each of the baseline nozzle afterbodies (no convolutions) had a parabolic, converging contour with a parabolically decreasing corner radius. Data were obtained at several Mach numbers from static conditions to 1.2 for a range of nozzle pressure ratios and angles of attack. An oil paint flow visualization technique was used to qualitatively assess the effect of the convolutions. Results indicate that afterbody drag reduction by convoluted contouring is convolution location, Mach number, boattail angle, and NPR dependent. The forward convolution location was the most effective contouring geometry for drag reduction on the 22 afterbody, but was only effective for M < 0.95. At M = 0.8, drag was reduced 20 and 36 percent at NPRs of 5.4 and 7, respectively, but drag was increased 10 percent for M = 0.95 at NPR = 7. Convoluted contouring along the 15 boattail angle afterbody was not effective at reducing drag because the flow was minimally separated from the baseline afterbody, unlike the massive separation along the 22 boattail angle baseline afterbody.

  7. Convolution modeling of two-domain, nonlinear water-level responses in karst aquifers (Invited)

    NASA Astrophysics Data System (ADS)

    Long, A. J.

    2009-12-01

    Convolution modeling is a useful method for simulating the hydraulic response of water levels to sinking streamflow or precipitation infiltration at the macro scale. This approach is particularly useful in karst aquifers, where the complex geometry of the conduit and pore network is not well characterized but can be represented approximately by a parametric impulse-response function (IRF) with very few parameters. For many applications, one-dimensional convolution models can be equally effective as complex two- or three-dimensional models for analyzing water-level responses to recharge. Moreover, convolution models are well suited for identifying and characterizing the distinct domains of quick flow and slow flow (e.g., conduit flow and diffuse flow). Two superposed lognormal functions were used in the IRF to approximate the impulses of the two flow domains. Nonlinear response characteristics of the flow domains were assessed by observing temporal changes in the IRFs. Precipitation infiltration was simulated by filtering the daily rainfall record with a backward-in-time exponential function that weights each day’s rainfall with the rainfall of previous days and thus accounts for the effects of soil moisture on aquifer infiltration. The model was applied to the Edwards aquifer in Texas and the Madison aquifer in South Dakota. Simulations of both aquifers showed similar characteristics, including a separation on the order of years between the quick-flow and slow-flow IRF peaks and temporal changes in the IRF shapes when water levels increased and empty pore spaces became saturated.

  8. Accurate segmentation of lung fields on chest radiographs using deep convolutional networks

    NASA Astrophysics Data System (ADS)

    Arbabshirani, Mohammad R.; Dallal, Ahmed H.; Agarwal, Chirag; Patel, Aalpan; Moore, Gregory

    2017-02-01

    Accurate segmentation of lung fields on chest radiographs is the primary step for computer-aided detection of various conditions such as lung cancer and tuberculosis. The size, shape and texture of lung fields are key parameters for chest X-ray (CXR) based lung disease diagnosis in which the lung field segmentation is a significant primary step. Although many methods have been proposed for this problem, lung field segmentation remains as a challenge. In recent years, deep learning has shown state of the art performance in many visual tasks such as object detection, image classification and semantic image segmentation. In this study, we propose a deep convolutional neural network (CNN) framework for segmentation of lung fields. The algorithm was developed and tested on 167 clinical posterior-anterior (PA) CXR images collected retrospectively from picture archiving and communication system (PACS) of Geisinger Health System. The proposed multi-scale network is composed of five convolutional and two fully connected layers. The framework achieved IOU (intersection over union) of 0.96 on the testing dataset as compared to manual segmentation. The suggested framework outperforms state of the art registration-based segmentation by a significant margin. To our knowledge, this is the first deep learning based study of lung field segmentation on CXR images developed on a heterogeneous clinical dataset. The results suggest that convolutional neural networks could be employed reliably for lung field segmentation.

  9. Robust smile detection using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Bianco, Simone; Celona, Luigi; Schettini, Raimondo

    2016-11-01

    We present a fully automated approach for smile detection. Faces are detected using a multiview face detector and aligned and scaled using automatically detected eye locations. Then, we use a convolutional neural network (CNN) to determine whether it is a smiling face or not. To this end, we investigate different shallow CNN architectures that can be trained even when the amount of learning data is limited. We evaluate our complete processing pipeline on the largest publicly available image database for smile detection in an uncontrolled scenario. We investigate the robustness of the method to different kinds of geometric transformations (rotation, translation, and scaling) due to imprecise face localization, and to several kinds of distortions (compression, noise, and blur). To the best of our knowledge, this is the first time that this type of investigation has been performed for smile detection. Experimental results show that our proposal outperforms state-of-the-art methods on both high- and low-quality images.

  10. Some partial-unit-memory convolutional codes

    NASA Technical Reports Server (NTRS)

    Abdel-Ghaffar, K.; Mceliece, R. J.; Solomon, G.

    1991-01-01

    The results of a study on a class of error correcting codes called partial unit memory (PUM) codes are presented. This class of codes, though not entirely new, has until now remained relatively unexplored. The possibility of using the well developed theory of block codes to construct a large family of promising PUM codes is shown. The performance of several specific PUM codes are compared with that of the Voyager standard (2, 1, 6) convolutional code. It was found that these codes can outperform the Voyager code with little or no increase in decoder complexity. This suggests that there may very well be PUM codes that can be used for deep space telemetry that offer both increased performance and decreased implementational complexity over current coding systems.

  11. Compressed imaging by sparse random convolution.

    PubMed

    Marcos, Diego; Lasser, Theo; López, Antonio; Bourquard, Aurélien

    2016-01-25

    The theory of compressed sensing (CS) shows that signals can be acquired at sub-Nyquist rates if they are sufficiently sparse or compressible. Since many images bear this property, several acquisition models have been proposed for optical CS. An interesting approach is random convolution (RC). In contrast with single-pixel CS approaches, RC allows for the parallel capture of visual information on a sensor array as in conventional imaging approaches. Unfortunately, the RC strategy is difficult to implement as is in practical settings due to important contrast-to-noise-ratio (CNR) limitations. In this paper, we introduce a modified RC model circumventing such difficulties by considering measurement matrices involving sparse non-negative entries. We then implement this model based on a slightly modified microscopy setup using incoherent light. Our experiments demonstrate the suitability of this approach for dealing with distinct CS scenarii, including 1-bit CS.

  12. Image statistics decoding for convolutional codes

    NASA Technical Reports Server (NTRS)

    Pitt, G. H., III; Swanson, L.; Yuen, J. H.

    1987-01-01

    It is a fact that adjacent pixels in a Voyager image are very similar in grey level. This fact can be used in conjunction with the Maximum-Likelihood Convolutional Decoder (MCD) to decrease the error rate when decoding a picture from Voyager. Implementing this idea would require no changes in the Voyager spacecraft and could be used as a backup to the current system without too much expenditure, so the feasibility of it and the possible gains for Voyager were investigated. Simulations have shown that the gain could be as much as 2 dB at certain error rates, and experiments with real data inspired new ideas on ways to get the most information possible out of the received symbol stream.

  13. Fully automated quantitative cephalometry using convolutional neural networks.

    PubMed

    Arık, Sercan Ö; Ibragimov, Bulat; Xing, Lei

    2017-01-01

    Quantitative cephalometry plays an essential role in clinical diagnosis, treatment, and surgery. Development of fully automated techniques for these procedures is important to enable consistently accurate computerized analyses. We study the application of deep convolutional neural networks (CNNs) for fully automated quantitative cephalometry for the first time. The proposed framework utilizes CNNs for detection of landmarks that describe the anatomy of the depicted patient and yield quantitative estimation of pathologies in the jaws and skull base regions. We use a publicly available cephalometric x-ray image dataset to train CNNs for recognition of landmark appearance patterns. CNNs are trained to output probabilistic estimations of different landmark locations, which are combined using a shape-based model. We evaluate the overall framework on the test set and compare with other proposed techniques. We use the estimated landmark locations to assess anatomically relevant measurements and classify them into different anatomical types. Overall, our results demonstrate high anatomical landmark detection accuracy ([Formula: see text] to 2% higher success detection rate for a 2-mm range compared with the top benchmarks in the literature) and high anatomical type classification accuracy ([Formula: see text] average classification accuracy for test set). We demonstrate that CNNs, which merely input raw image patches, are promising for accurate quantitative cephalometry.

  14. Building Extraction from Remote Sensing Data Using Fully Convolutional Networks

    NASA Astrophysics Data System (ADS)

    Bittner, K.; Cui, S.; Reinartz, P.

    2017-05-01

    Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building footprints still remains a nontrivial topic, especially in complex urban areas. Recently developed extensions of the CNN framework made it possible to perform dense pixel-wise classification of input images. Based on these abilities we propose a methodology, which automatically generates a full resolution binary building mask out of a Digital Surface Model (DSM) using a Fully Convolution Network (FCN) architecture. The advantage of using the depth information is that it provides geometrical silhouettes and allows a better separation of buildings from background as well as through its invariance to illumination and color variations. The proposed framework has mainly two steps. Firstly, the FCN is trained on a large set of patches consisting of normalized DSM (nDSM) as inputs and available ground truth building mask as target outputs. Secondly, the generated predictions from FCN are viewed as unary terms for a Fully connected Conditional Random Fields (FCRF), which enables us to create a final binary building mask. A series of experiments demonstrate that our methodology is able to extract accurate building footprints which are close to the buildings original shapes to a high degree. The quantitative and qualitative analysis show the significant improvements of the results in contrast to the multy-layer fully connected network from our previous work.

  15. Multi-modal vertebrae recognition using Transformed Deep Convolution Network.

    PubMed

    Cai, Yunliang; Landis, Mark; Laidley, David T; Kornecki, Anat; Lum, Andrea; Li, Shuo

    2016-07-01

    Automatic vertebra recognition, including the identification of vertebra locations and naming in multiple image modalities, are highly demanded in spinal clinical diagnoses where large amount of imaging data from various of modalities are frequently and interchangeably used. However, the recognition is challenging due to the variations of MR/CT appearances or shape/pose of the vertebrae. In this paper, we propose a method for multi-modal vertebra recognition using a novel deep learning architecture called Transformed Deep Convolution Network (TDCN). This new architecture can unsupervisely fuse image features from different modalities and automatically rectify the pose of vertebra. The fusion of MR and CT image features improves the discriminativity of feature representation and enhances the invariance of the vertebra pattern, which allows us to automatically process images from different contrast, resolution, protocols, even with different sizes and orientations. The feature fusion and pose rectification are naturally incorporated in a multi-layer deep learning network. Experiment results show that our method outperforms existing detection methods and provides a fully automatic location+naming+pose recognition for routine clinical practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Convolution models for induced electromagnetic responses

    PubMed Central

    Litvak, Vladimir; Jha, Ashwani; Flandin, Guillaume; Friston, Karl

    2013-01-01

    In Kilner et al. [Kilner, J.M., Kiebel, S.J., Friston, K.J., 2005. Applications of random field theory to electrophysiology. Neurosci. Lett. 374, 174–178.] we described a fairly general analysis of induced responses—in electromagnetic brain signals—using the summary statistic approach and statistical parametric mapping. This involves localising induced responses—in peristimulus time and frequency—by testing for effects in time–frequency images that summarise the response of each subject to each trial type. Conventionally, these time–frequency summaries are estimated using post‐hoc averaging of epoched data. However, post‐hoc averaging of this sort fails when the induced responses overlap or when there are multiple response components that have variable timing within each trial (for example stimulus and response components associated with different reaction times). In these situations, it is advantageous to estimate response components using a convolution model of the sort that is standard in the analysis of fMRI time series. In this paper, we describe one such approach, based upon ordinary least squares deconvolution of induced responses to input functions encoding the onset of different components within each trial. There are a number of fundamental advantages to this approach: for example; (i) one can disambiguate induced responses to stimulus onsets and variably timed responses; (ii) one can test for the modulation of induced responses—over peristimulus time and frequency—by parametric experimental factors and (iii) one can gracefully handle confounds—such as slow drifts in power—by including them in the model. In what follows, we consider optimal forms for convolution models of induced responses, in terms of impulse response basis function sets and illustrate the utility of deconvolution estimators using simulated and real MEG data. PMID:22982359

  17. Development of an LSI maximum-likelihood convolutional decoder for advanced forward error correction capability on the NASA 30/20 GHz program

    NASA Technical Reports Server (NTRS)

    Clark, R. T.; Mccallister, R. D.

    1982-01-01

    The particular coding option identified as providing the best level of coding gain performance in an LSI-efficient implementation was the optimal constraint length five, rate one-half convolutional code. To determine the specific set of design parameters which optimally matches this decoder to the LSI constraints, a breadboard MCD (maximum-likelihood convolutional decoder) was fabricated and used to generate detailed performance trade-off data. The extensive performance testing data gathered during this design tradeoff study are summarized, and the functional and physical MCD chip characteristics are presented.

  18. Image quality of mixed convolution kernel in thoracic computed tomography

    PubMed Central

    Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

    2016-01-01

    Abstract The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images. Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test. Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001). The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT. PMID:27858910

  19. Image quality of mixed convolution kernel in thoracic computed tomography.

    PubMed

    Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

    2016-11-01

    The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

  20. Convolution kernel design and efficient algorithm for sampling density correction.

    PubMed

    Johnson, Kenneth O; Pipe, James G

    2009-02-01

    Sampling density compensation is an important step in non-cartesian image reconstruction. One of the common techniques to determine weights that compensate for differences in sampling density involves a convolution. A new convolution kernel is designed for sampling density attempting to minimize the error in a fully reconstructed image. The resulting weights obtained using this new kernel are compared with various previous methods, showing a reduction in reconstruction error. A computationally efficient algorithm is also presented that facilitates the calculation of the convolution of finite kernels. Both the kernel and the algorithm are extended to 3D. Copyright 2009 Wiley-Liss, Inc.

  1. Programmable convolution via the chirp Z-transform with CCD's

    NASA Technical Reports Server (NTRS)

    Buss, D. D.

    1977-01-01

    Technique filtering by convolution in frequency domain rather than in time domain presents possible solution to problem of programmable transversal filters. Process is accomplished through utilization of chip z-transform (CZT) with charge-coupled devices

  2. Model Convolution: A Computational Approach to Digital Image Interpretation.

    PubMed

    Gardner, Melissa K; Sprague, Brian L; Pearson, Chad G; Cosgrove, Benjamin D; Bicek, Andrew D; Bloom, Kerry; Salmon, E D; Odde, David J

    2010-06-01

    Digital fluorescence microscopy is commonly used to track individual proteins and their dynamics in living cells. However, extracting molecule-specific information from fluorescence images is often limited by the noise and blur intrinsic to the cell and the imaging system. Here we discuss a method called "model-convolution," which uses experimentally measured noise and blur to simulate the process of imaging fluorescent proteins whose spatial distribution cannot be resolved. We then compare model-convolution to the more standard approach of experimental deconvolution. In some circumstances, standard experimental deconvolution approaches fail to yield the correct underlying fluorophore distribution. In these situations, model-convolution removes the uncertainty associated with deconvolution and therefore allows direct statistical comparison of experimental and theoretical data. Thus, if there are structural constraints on molecular organization, the model-convolution method better utilizes information gathered via fluorescence microscopy, and naturally integrates experiment and theory.

  3. A fast computation of complex convolution using a hybrid transform

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1978-01-01

    The cyclic convolution of complex values was obtained by a hybrid transform that is a combination of a Winograd transform and a fast complex integer transform. This new hybrid algorithm requires fewer multiplications than any previously known algorithm.

  4. Programmable convolution via the chirp Z-transform with CCD's

    NASA Technical Reports Server (NTRS)

    Buss, D. D.

    1977-01-01

    Technique filtering by convolution in frequency domain rather than in time domain presents possible solution to problem of programmable transversal filters. Process is accomplished through utilization of chip z-transform (CZT) with charge-coupled devices

  5. Model Convolution: A Computational Approach to Digital Image Interpretation

    PubMed Central

    Gardner, Melissa K.; Sprague, Brian L.; Pearson, Chad G.; Cosgrove, Benjamin D.; Bicek, Andrew D.; Bloom, Kerry; Salmon, E. D.

    2010-01-01

    Digital fluorescence microscopy is commonly used to track individual proteins and their dynamics in living cells. However, extracting molecule-specific information from fluorescence images is often limited by the noise and blur intrinsic to the cell and the imaging system. Here we discuss a method called “model-convolution,” which uses experimentally measured noise and blur to simulate the process of imaging fluorescent proteins whose spatial distribution cannot be resolved. We then compare model-convolution to the more standard approach of experimental deconvolution. In some circumstances, standard experimental deconvolution approaches fail to yield the correct underlying fluorophore distribution. In these situations, model-convolution removes the uncertainty associated with deconvolution and therefore allows direct statistical comparison of experimental and theoretical data. Thus, if there are structural constraints on molecular organization, the model-convolution method better utilizes information gathered via fluorescence microscopy, and naturally integrates experiment and theory. PMID:20461132

  6. Sizing-up finite fluorescent particles with nanometer-scale precision by convolution and correlation image analysis.

    PubMed

    Gennerich, Arne; Schild, Detlev

    2005-05-01

    Determining the positions, shapes and sizes of finite living particles such as bacteria, mitochondria or vesicles is of interest in many biological processes. In fluorescence microscopy, algorithms that can simultaneously localize such particles as a function of time and determine the parameters of their shapes and sizes at the nanometer scale are not yet available. Here we develop two such algorithms based on convolution and correlation image analysis that take into account the position, orientation, shape and size of the object being tracked, and we compare the precision of the two algorithms using computer simulations. We show that the precision of both algorithms strongly depends on the object's size. In cases where the diameter of the object is larger than about four to five times the beam waist radius, the convolution algorithm gives a better precision than the correlation algorithm (it leads to more precise parameters), while for smaller object diameters, the correlation algorithm gives superior precision. We apply the convolution algorithm to sequences of confocal laser scanning micrographs of immobile Escherichia coli bacteria, and show that the centroid, the front end, the rear end, the left border and the right border of a bacterium can be determined with a signal-to-noise-dependent precision down to approximately 5 nm.

  7. Radial Structure Scaffolds Convolution Patterns of Developing Cerebral Cortex

    PubMed Central

    Razavi, Mir Jalil; Zhang, Tuo; Chen, Hanbo; Li, Yujie; Platt, Simon; Zhao, Yu; Guo, Lei; Hu, Xiaoping; Wang, Xianqiao; Liu, Tianming

    2017-01-01

    Commonly-preserved radial convolution is a prominent characteristic of the mammalian cerebral cortex. Endeavors from multiple disciplines have been devoted for decades to explore the causes for this enigmatic structure. However, the underlying mechanisms that lead to consistent cortical convolution patterns still remain poorly understood. In this work, inspired by prior studies, we propose and evaluate a plausible theory that radial convolution during the early development of the brain is sculptured by radial structures consisting of radial glial cells (RGCs) and maturing axons. Specifically, the regionally heterogeneous development and distribution of RGCs controlled by Trnp1 regulate the convex and concave convolution patterns (gyri and sulci) in the radial direction, while the interplay of RGCs' effects on convolution and axons regulates the convex (gyral) convolution patterns. This theory is assessed by observations and measurements in literature from multiple disciplines such as neurobiology, genetics, biomechanics, etc., at multiple scales to date. Particularly, this theory is further validated by multimodal imaging data analysis and computational simulations in this study. We offer a versatile and descriptive study model that can provide reasonable explanations of observations, experiments, and simulations of the characteristic mammalian cortical folding. PMID:28860983

  8. Radial Structure Scaffolds Convolution Patterns of Developing Cerebral Cortex.

    PubMed

    Razavi, Mir Jalil; Zhang, Tuo; Chen, Hanbo; Li, Yujie; Platt, Simon; Zhao, Yu; Guo, Lei; Hu, Xiaoping; Wang, Xianqiao; Liu, Tianming

    2017-01-01

    Commonly-preserved radial convolution is a prominent characteristic of the mammalian cerebral cortex. Endeavors from multiple disciplines have been devoted for decades to explore the causes for this enigmatic structure. However, the underlying mechanisms that lead to consistent cortical convolution patterns still remain poorly understood. In this work, inspired by prior studies, we propose and evaluate a plausible theory that radial convolution during the early development of the brain is sculptured by radial structures consisting of radial glial cells (RGCs) and maturing axons. Specifically, the regionally heterogeneous development and distribution of RGCs controlled by Trnp1 regulate the convex and concave convolution patterns (gyri and sulci) in the radial direction, while the interplay of RGCs' effects on convolution and axons regulates the convex (gyral) convolution patterns. This theory is assessed by observations and measurements in literature from multiple disciplines such as neurobiology, genetics, biomechanics, etc., at multiple scales to date. Particularly, this theory is further validated by multimodal imaging data analysis and computational simulations in this study. We offer a versatile and descriptive study model that can provide reasonable explanations of observations, experiments, and simulations of the characteristic mammalian cortical folding.

  9. Fabrication of cross-shaped Cu-nanowire resistive memory devices using a rapid, scalable, and designable inorganic-nanowire-digital-alignment technique (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Xu, Wentao; Lee, Yeongjun; Min, Sung-Yong; Park, Cheolmin; Lee, Tae-Woo

    2016-09-01

    Resistive random-access memory (RRAM) is a candidate next generation nonvolatile memory due to its high access speed, high density and ease of fabrication. Especially, cross-point-access allows cross-bar arrays that lead to high-density cells in a two-dimensional planar structure. Use of such designs could be compatible with the aggressive scaling down of memory devices, but existing methods such as optical or e-beam lithographic approaches are too complicated. One-dimensional inorganic nanowires (i-NWs) are regarded as ideal components of nanoelectronics to circumvent the limitations of conventional lithographic approaches. However, post-growth alignment of these i-NWs precisely on a large area with individual control is still a difficult challenge. Here, we report a simple, inexpensive, and rapid method to fabricate two-dimensional arrays of perpendicularly-aligned, individually-conductive Cu-NWs with a nanometer-scale CuxO layer sandwiched at each cross point, by using an inorganic-nanowire-digital-alignment technique (INDAT) and a one-step reduction process. In this approach, the oxide layer is self-formed and patterned, so conventional deposition and lithography are not necessary. INDAT eliminates the difficulties of alignment and scalable fabrication that are encountered when using currently-available techniques that use inorganic nanowires. This simple process facilitates fabrication of cross-point nonvolatile memristor arrays. Fabricated arrays had reproducible resistive switching behavior, high on/off current ratio (Ion/Ioff) 10 6 and extensive cycling endurance. This is the first report of memristors with the resistive switching oxide layer self-formed, self-patterned and self-positioned; we envision that the new features of the technique will provide great opportunities for future nano-electronic circuits.

  10. Convolution kernels for multi-wavelength imaging

    NASA Astrophysics Data System (ADS)

    Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.

    2016-12-01

    Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher

  11. Piano Transcription with Convolutional Sparse Lateral Inhibition

    DOE PAGES

    Cogliati, Andrea; Duan, Zhiyao; Wohlberg, Brendt Egon

    2017-02-08

    This paper extends our prior work on contextdependent piano transcription to estimate the length of the notes in addition to their pitch and onset. This approach employs convolutional sparse coding along with lateral inhibition constraints to approximate a musical signal as the sum of piano note waveforms (dictionary elements) convolved with their temporal activations. The waveforms are pre-recorded for the specific piano to be transcribed in the specific environment. A dictionary containing multiple waveforms per pitch is generated by truncating a long waveform for each pitch to different lengths. During transcription, the dictionary elements are fixed and their temporal activationsmore » are estimated and post-processed to obtain the pitch, onset and note length estimation. A sparsity penalty promotes globally sparse activations of the dictionary elements, and a lateral inhibition term penalizes concurrent activations of different waveforms corresponding to the same pitch within a temporal neighborhood, to achieve note length estimation. Experiments on the MAPS dataset show that the proposed approach significantly outperforms a state-of-the-art music transcription method trained in the same context-dependent setting in transcription accuracy.« less

  12. Event Discrimination using Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Menon, Hareesh; Hughes, Richard; Daling, Alec; Winer, Brian

    2017-01-01

    Convolutional Neural Networks (CNNs) are computational models that have been shown to be effective at classifying different types of images. We present a method to use CNNs to distinguish events involving the production of a top quark pair and a Higgs boson from events involving the production of a top quark pair and several quark and gluon jets. To do this, we generate and simulate data using MADGRAPH and DELPHES for a general purpose LHC detector at 13 TeV. We produce images using a particle flow algorithm by binning the particles geometrically based on their position in the detector and weighting the bins by the energy of each particle within each bin, and by defining channels based on particle types (charged track, neutral hadronic, neutral EM, lepton, heavy flavor). Our classification results are competitive with standard machine learning techniques. We have also looked into the classification of the substructure of the events, in a process known as scene labeling. In this context, we look for the presence of boosted objects (such as top quarks) with substructure encompassed within single jets. Preliminary results on substructure classification will be presented.

  13. Accelerated unsteady flow line integral convolution.

    PubMed

    Liu, Zhanping; Moorhead, Robert J

    2005-01-01

    Unsteady flow line integral convolution (UFLIC) is a texture synthesis technique for visualizing unsteady flows with high temporal-spatial coherence. Unfortunately, UFLIC requires considerable time to generate each frame due to the huge amount of pathline integration that is computed for particle value scattering. This paper presents Accelerated UFLIC (AUFLIC) for near interactive (1 frame/second) visualization with 160,000 particles per frame. AUFLIC reuses pathlines in the value scattering process to reduce computationally expensive pathline integration. A flow-driven seeding strategy is employed to distribute seeds such that only a few of them need pathline integration while most seeds are placed along the pathlines advected at earlier times by other seeds upstream and, therefore, the known pathlines can be reused for fast value scattering. To maintain a dense scattering coverage to convey high temporal-spatial coherence while keeping the expense of pathline integration low, a dynamic seeding controller is designed to decide whether to advect, copy, or reuse a pathline. At a negligible memory cost, AUFLIC is 9 times faster than UFLIC with comparable image quality.

  14. Do Convolutional Neural Networks Learn Class Hierarchy?

    PubMed

    Alsallakh, Bilal; Jourabloo, Amin; Ye, Mao; Liu, Xiaoming; Ren, Liu

    2017-08-29

    Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.

  15. Metaheuristic Algorithms for Convolution Neural Network

    PubMed Central

    Fanany, Mohamad Ivan; Arymurthy, Aniati Murni

    2016-01-01

    A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent). PMID:27375738

  16. Metaheuristic Algorithms for Convolution Neural Network.

    PubMed

    Rere, L M Rasdi; Fanany, Mohamad Ivan; Arymurthy, Aniati Murni

    2016-01-01

    A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent).

  17. Dispersion-convolution model for simulating peaks in a flow injection system.

    PubMed

    Pai, Su-Cheng; Lai, Yee-Hwong; Chiao, Ling-Yun; Yu, Tiing

    2007-01-12

    A dispersion-convolution model is proposed for simulating peak shapes in a single-line flow injection system. It is based on the assumption that an injected sample plug is expanded due to a "bulk" dispersion mechanism along the length coordinate, and that after traveling over a distance or a period of time, the sample zone will develop into a Gaussian-like distribution. This spatial pattern is further transformed to a temporal coordinate by a convolution process, and finally a temporal peak image is generated. The feasibility of the proposed model has been examined by experiments with various coil lengths, sample sizes and pumping rates. An empirical dispersion coefficient (D*) can be estimated by using the observed peak position, height and area (tp*, h* and At*) from a recorder. An empirical temporal shift (Phi*) can be further approximated by Phi*=D*/u2, which becomes an important parameter in the restoration of experimental peaks. Also, the dispersion coefficient can be expressed as a second-order polynomial function of the pumping rate Q, for which D*(Q)=delta0+delta1Q+delta2Q2. The optimal dispersion occurs at a pumping rate of Qopt=sqrt[delta0/delta2]. This explains the interesting "Nike-swoosh" relationship between the peak height and pumping rate. The excellent coherence of theoretical and experimental peak shapes confirms that the temporal distortion effect is the dominating reason to explain the peak asymmetry in flow injection analysis.

  18. Fourier deconvolution reveals the role of the Lorentz function as the convolution kernel of narrow photon beams.

    PubMed

    Djouguela, Armand; Harder, Dietrich; Kollhoff, Ralf; Foschepoth, Simon; Kunth, Wolfgang; Rühmann, Antje; Willborn, Kay; Poppe, Björn

    2009-05-07

    The two-dimensional lateral dose profiles D(x, y) of narrow photon beams, typically used for beamlet-based IMRT, stereotactic radiosurgery and tomotherapy, can be regarded as resulting from the convolution of a two-dimensional rectangular function R(x, y), which represents the photon fluence profile within the field borders, with a rotation-symmetric convolution kernel K(r). This kernel accounts not only for the lateral transport of secondary electrons and small-angle scattered photons in the absorber, but also for the 'geometrical spread' of each pencil beam due to the phase-space distribution of the photon source. The present investigation of the convolution kernel was based on an experimental study of the associated line-spread function K(x). Systematic cross-plane scans of rectangular and quadratic fields of variable side lengths were made by utilizing the linear current versus dose rate relationship and small energy dependence of the unshielded Si diode PTW 60012 as well as its narrow spatial resolution function. By application of the Fourier convolution theorem, it was observed that the values of the Fourier transform of K(x) could be closely fitted by an exponential function exp(-2pilambdanu(x)) of the spatial frequency nu(x). Thereby, the line-spread function K(x) was identified as the Lorentz function K(x) = (lambda/pi)[1/(x(2) + lambda(2))], a single-parameter, bell-shaped but non-Gaussian function with a narrow core, wide curve tail, full half-width 2lambda and convenient convolution properties. The variation of the 'kernel width parameter' lambda with the photon energy, field size and thickness of a water-equivalent absorber was systematically studied. The convolution of a rectangular fluence profile with K(x) in the local space results in a simple equation accurately reproducing the measured lateral dose profiles. The underlying 2D convolution kernel (point-spread function) was identified as K(r) = (lambda/2pi)[1/(r(2) + lambda(2))](3/2), fitting

  19. Colonoscopic polyp detection using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Park, Sun Young; Sargent, Dusty

    2016-03-01

    Computer aided diagnosis (CAD) systems for medical image analysis rely on accurate and efficient feature extraction methods. Regardless of which type of classifier is used, the results will be limited if the input features are not diagnostically relevant and do not properly discriminate between the different classes of images. Thus, a large amount of research has been dedicated to creating feature sets that capture the salient features that physicians are able to observe in the images. Successful feature extraction reduces the semantic gap between the physician's interpretation and the computer representation of images, and helps to reduce the variability in diagnosis between physicians. Due to the complexity of many medical image classification tasks, feature extraction for each problem often requires domainspecific knowledge and a carefully constructed feature set for the specific type of images being classified. In this paper, we describe a method for automatic diagnostic feature extraction from colonoscopy images that may have general application and require a lower level of domain-specific knowledge. The work in this paper expands on our previous CAD algorithm for detecting polyps in colonoscopy video. In that work, we applied an eigenimage model to extract features representing polyps, normal tissue, diverticula, etc. from colonoscopy videos taken from various viewing angles and imaging conditions. Classification was performed using a conditional random field (CRF) model that accounted for the spatial and temporal adjacency relationships present in colonoscopy video. In this paper, we replace the eigenimage feature descriptor with features extracted from a convolutional neural network (CNN) trained to recognize the same image types in colonoscopy video. The CNN-derived features show greater invariance to viewing angles and image quality factors when compared to the eigenimage model. The CNN features are used as input to the CRF classifier as before. We report

  20. Noise-enhanced convolutional neural networks.

    PubMed

    Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

    2016-06-01

    Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Brain and art: illustrations of the cerebral convolutions. A review.

    PubMed

    Lazić, D; Marinković, S; Tomić, I; Mitrović, D; Starčević, A; Milić, I; Grujičić, M; Marković, B

    2014-08-01

    Aesthetics and functional significance of the cerebral cortical relief gave us the idea to find out how often the convolutions are presented in fine art, and in which techniques, conceptual meaning and pathophysiological aspect. We examined 27,614 art works created by 2,856 authors and presented in art literature, and in Google images search. The cerebral gyri were shown in 0.85% of the art works created by 2.35% of the authors. The concept of the brain was first mentioned in ancient Egypt some 3,700 years ago. The first artistic drawing of the convolutions was made by Leonardo da Vinci, and the first colour picture by an unknown Italian author. Rembrandt van Rijn was the first to paint the gyri. Dozens of modern authors, who are professional artists, medical experts or designers, presented the cerebralc onvolutions in drawings, paintings, digital works or sculptures, with various aesthetic, symbolic and metaphorical connotation. Some artistic compositions and natural forms show a gyral pattern. The convolutions, whose cortical layers enable the cognitive functions, can be affected by various disorders. Some artists suffered from those disorders, and some others presented them in their artworks. The cerebral convolutions or gyri, thanks to their extensive cortical mantle, are the specific morphological basis for the human mind, but also the structures with their own aesthetics. Contemporary authors relatively often depictor model the cerebral convolutions, either from the aesthetic or conceptual aspect. In this way, they make a connection between the neuroscience and fineart.

  2. Inequalities and consequences of new convolutions for the fractional Fourier transform with Hermite weights

    NASA Astrophysics Data System (ADS)

    Anh, P. K.; Castro, L. P.; Thao, P. T.; Tuan, N. M.

    2017-01-01

    This paper presents new convolutions for the fractional Fourier transform which are somehow associated with the Hermite functions. Consequent inequalities and properties are derived for these convolutions, among which we emphasize two new types of Young's convolution inequalities. The results guarantee a general framework where the present convolutions are well-defined, allowing larger possibilities than the known ones for other convolutions. Furthermore, we exemplify the use of our convolutions by providing explicit solutions of some classes of integral equations which appear in engineering problems.

  3. Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features With Structure Preservation on 3-D Meshes.

    PubMed

    Han, Zhizhong; Liu, Zhenbao; Han, Junwei; Vong, Chi-Man; Bu, Shuhui; Chen, Chun Long Philip

    2016-06-30

    Discriminative features of 3-D meshes are significant to many 3-D shape analysis tasks. However, handcrafted descriptors and traditional unsupervised 3-D feature learning methods suffer from several significant weaknesses: 1) the extensive human intervention is involved; 2) the local and global structure information of 3-D meshes cannot be preserved, which is in fact an important source of discriminability; 3) the irregular vertex topology and arbitrary resolution of 3-D meshes do not allow the direct application of the popular deep learning models; 4) the orientation is ambiguous on the mesh surface; and 5) the effect of rigid and nonrigid transformations on 3-D meshes cannot be eliminated. As a remedy, we propose a deep learning model with a novel irregular model structure, called mesh convolutional restricted Boltzmann machines (MCRBMs). MCRBM aims to simultaneously learn structure-preserving local and global features from a novel raw representation, local function energy distribution. In addition, multiple MCRBMs can be stacked into a deeper model, called mesh convolutional deep belief networks (MCDBNs). MCDBN employs a novel local structure preserving convolution (LSPC) strategy to convolve the geometry and the local structure learned by the lower MCRBM to the upper MCRBM. LSPC facilitates resolving the challenging issue of the orientation ambiguity on the mesh surface in MCDBN. Experiments using the proposed MCRBM and MCDBN were conducted on three common aspects: global shape retrieval, partial shape retrieval, and shape correspondence. Results show that the features learned by the proposed methods outperform the other state-of-the-art 3-D shape features.

  4. Design, fabrication, and characterization of a planar, silicon-based, monolithically integrated micro laminar flow fuel cell with a bridge-shaped microchannel cross-section

    NASA Astrophysics Data System (ADS)

    López-Montesinos, P. O.; Yossakda, N.; Schmidt, A.; Brushett, F. R.; Pelton, W. E.; Kenis, P. J. A.

    2011-05-01

    We report the fabrication of a planar, silicon-based, monolithically integrated micro laminar flow fuel cell (μLFFC) using standard MEMS and IC-compatible fabrication technologies. The μLFFC operates with acid supported solutions of formic acid and potassium permanganate, as a fuel and oxidant respectively. The micro-fuel cell design features two in-plane anodic and cathodic microchannels connected via a bridge to confine the diffusive liquid-liquid interface away from the electrode areas and to minimize crossover. Palladium high-active-surface-area catalyst was selectively integrated into the anodic microchannel by electrodeposition, whereas no catalyst was required in the cathodic microchannel. A three-dimensional (3D) diffusion-convection model was developed to study the behavior of the diffusion zone and to extract appropriate cell-design parameters and operating conditions. Experimentally, we observed peak power densities as high as 26 mW cm-2 when operating single cells at a flow rate of 60 μL min-1 at room temperature. The miniature membraneless fuel cell design presented herein offers potential for on-chip power generation, which has long been prohibited by integration complexities associated with the membrane.

  5. Model-based optoacoustic inversion with arbitrary-shape detectors.

    PubMed

    Rosenthal, Amir; Ntziachristos, Vasilis; Razansky, Daniel

    2011-07-01

    Optoacoustic imaging enables mapping the optical absorption of biological tissue using optical excitation and acoustic detection. Although most image-reconstruction algorithms are based on the assumption of a detector with an isotropic sensitivity, the geometry of the detector often leads to a response with spatially dependent magnitude and bandwidth. This effect may lead to attenuation or distortion in the recorded signal and, consequently, in the reconstructed image. Herein, an accurate numerical method for simulating the spatially dependent response of an arbitrary-shape acoustic transducer is presented. The method is based on an analytical solution obtained for a two-dimensional line detector. The calculated response is incorporated in the forward model matrix of an optoacoustic imaging setup using temporal convolution, and image reconstruction is performed by inverting the matrix relation. The method was numerically and experimentally demonstrated in two dimensions for both flat and focused transducers and compared to the spatial-convolution method. In forward simulations, the developed method did not suffer from the numerical errors exhibited by the spatial-convolution method. In reconstruction simulations and experiments, the use of both temporal-convolution and spatial-convolution methods lead to an enhancement in resolution compared to a reconstruction with a point detector model. However, because of its higher modeling accuracy, the temporal-convolution method achieved a noise figure approximated three times lower than the spatial-convolution method. The demonstrated performance of the spatial-convolution method shows it is a powerful tool for reducing reconstruction artifacts originating from the detector finite size and improving the quality of optoacoustic reconstructions. Furthermore, the method may be used for assessing new system designs. Specifically, detectors with nonstandard shapes may be investigated.

  6. Knowledge Based 3d Building Model Recognition Using Convolutional Neural Networks from LIDAR and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Alidoost, F.; Arefi, H.

    2016-06-01

    In recent years, with the development of the high resolution data acquisition technologies, many different approaches and algorithms have been presented to extract the accurate and timely updated 3D models of buildings as a key element of city structures for numerous applications in urban mapping. In this paper, a novel and model-based approach is proposed for automatic recognition of buildings' roof models such as flat, gable, hip, and pyramid hip roof models based on deep structures for hierarchical learning of features that are extracted from both LiDAR and aerial ortho-photos. The main steps of this approach include building segmentation, feature extraction and learning, and finally building roof labeling in a supervised pre-trained Convolutional Neural Network (CNN) framework to have an automatic recognition system for various types of buildings over an urban area. In this framework, the height information provides invariant geometric features for convolutional neural network to localize the boundary of each individual roofs. CNN is a kind of feed-forward neural network with the multilayer perceptron concept which consists of a number of convolutional and subsampling layers in an adaptable structure and it is widely used in pattern recognition and object detection application. Since the training dataset is a small library of labeled models for different shapes of roofs, the computation time of learning can be decreased significantly using the pre-trained models. The experimental results highlight the effectiveness of the deep learning approach to detect and extract the pattern of buildings' roofs automatically considering the complementary nature of height and RGB information.

  7. Spatially variant convolution with scaled B-splines.

    PubMed

    Muñoz-Barrutia, Arrate; Artaechevarria, Xabier; Ortiz-de-Solorzano, Carlos

    2010-01-01

    We present an efficient algorithm to compute multidimensional spatially variant convolutions--or inner products--between N-dimensional signals and B-splines--or their derivatives--of any order and arbitrary sizes. The multidimensional B-splines are computed as tensor products of 1-D B-splines, and the input signal is expressed in a B-spline basis. The convolution is then computed by using an adequate combination of integration and scaled finite differences as to have, for moderate and large scale values, a computational complexity that does not depend on the scaling factor. To show in practice the benefit of using our spatially variant convolution approach, we present an adaptive noise filter that adjusts the kernel size to the local image characteristics and a high sensitivity local ridge detector.

  8. Two dimensional convolute integers for machine vision and image recognition

    NASA Technical Reports Server (NTRS)

    Edwards, Thomas R.

    1988-01-01

    Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.

  9. Two dimensional convolute integers for machine vision and image recognition

    NASA Technical Reports Server (NTRS)

    Edwards, Thomas R.

    1988-01-01

    Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.

  10. Error-trellis syndrome decoding techniques for convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1985-01-01

    An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decordig is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

  11. Error-trellis Syndrome Decoding Techniques for Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1984-01-01

    An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decoding is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

  12. Error-trellis syndrome decoding techniques for convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1985-01-01

    An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decordig is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

  13. Bioprinting of 3D Convoluted Renal Proximal Tubules on Perfusable Chips

    PubMed Central

    Homan, Kimberly A.; Kolesky, David B.; Skylar-Scott, Mark A.; Herrmann, Jessica; Obuobi, Humphrey; Moisan, Annie; Lewis, Jennifer A.

    2016-01-01

    Three-dimensional models of kidney tissue that recapitulate human responses are needed for drug screening, disease modeling, and, ultimately, kidney organ engineering. Here, we report a bioprinting method for creating 3D human renal proximal tubules in vitro that are fully embedded within an extracellular matrix and housed in perfusable tissue chips, allowing them to be maintained for greater than two months. Their convoluted tubular architecture is circumscribed by proximal tubule epithelial cells and actively perfused through the open lumen. These engineered 3D proximal tubules on chip exhibit significantly enhanced epithelial morphology and functional properties relative to the same cells grown on 2D controls with or without perfusion. Upon introducing the nephrotoxin, Cyclosporine A, the epithelial barrier is disrupted in a dose-dependent manner. Our bioprinting method provides a new route for programmably fabricating advanced human kidney tissue models on demand. PMID:27725720

  14. Bioprinting of 3D Convoluted Renal Proximal Tubules on Perfusable Chips

    NASA Astrophysics Data System (ADS)

    Homan, Kimberly A.; Kolesky, David B.; Skylar-Scott, Mark A.; Herrmann, Jessica; Obuobi, Humphrey; Moisan, Annie; Lewis, Jennifer A.

    2016-10-01

    Three-dimensional models of kidney tissue that recapitulate human responses are needed for drug screening, disease modeling, and, ultimately, kidney organ engineering. Here, we report a bioprinting method for creating 3D human renal proximal tubules in vitro that are fully embedded within an extracellular matrix and housed in perfusable tissue chips, allowing them to be maintained for greater than two months. Their convoluted tubular architecture is circumscribed by proximal tubule epithelial cells and actively perfused through the open lumen. These engineered 3D proximal tubules on chip exhibit significantly enhanced epithelial morphology and functional properties relative to the same cells grown on 2D controls with or without perfusion. Upon introducing the nephrotoxin, Cyclosporine A, the epithelial barrier is disrupted in a dose-dependent manner. Our bioprinting method provides a new route for programmably fabricating advanced human kidney tissue models on demand.

  15. Spectral interpolation - Zero fill or convolution. [image processing

    NASA Technical Reports Server (NTRS)

    Forman, M. L.

    1977-01-01

    Zero fill, or augmentation by zeros, is a method used in conjunction with fast Fourier transforms to obtain spectral spacing at intervals closer than obtainable from the original input data set. In the present paper, an interpolation technique (interpolation by repetitive convolution) is proposed which yields values accurate enough for plotting purposes and which lie within the limits of calibration accuracies. The technique is shown to operate faster than zero fill, since fewer operations are required. The major advantages of interpolation by repetitive convolution are that efficient use of memory is possible (thus avoiding the difficulties encountered in decimation in time FFTs) and that is is easy to implement.

  16. Fabrication of a Kevlar liner assembly

    SciTech Connect

    Schloman, A.H.

    1980-07-01

    Several liner assemblies were fabricated with Kevlar 49 and epoxy using various wet layup and prepreg processes. A production process, using prepreg material, was developed for fabricating the liner and a wet layup molding process was used to fabricate the Kevlar hat-shaped tunnels. Fabrication of the tunnels using Kevlar prepreg with an autoclave curving process was evaluated.

  17. Projection of fMRI data onto the cortical surface using anatomically-informed convolution kernels.

    PubMed

    Operto, G; Bulot, R; Anton, J-L; Coulon, O

    2008-01-01

    As surface-based data analysis offer an attractive approach for intersubject matching and comparison, the projection of voxel-based 3D volumes onto the cortical surface is an essential problem. We present here a method that aims at producing representations of functional brain data on the cortical surface from functional MRI volumes. Such representations are for instance required for subsequent cortical-based functional analysis. We propose a projection technique based on the definition, around each node of the gray/white matter interface mesh, of convolution kernels whose shape and distribution rely on the geometry of the local anatomy. For one anatomy, a set of convolution kernels is computed that can be used to project any functional data registered with this anatomy. Therefore resulting in anatomically-informed projections of data onto the cortical surface, this kernel-based approach offers better sensitivity, specificity than other classical methods and robustness to misregistration errors. Influences of mesh and volumes spatial resolutions were also estimated for various projection techniques, using simulated functional maps.

  18. Voltage measurements at the vacuum post-hole convolute of the Z pulsed-power accelerator

    SciTech Connect

    Waisman, E. M.; McBride, R. D.; Cuneo, M. E.; Wenger, D. F.; Fowler, W. E.; Johnson, W. A.; Basilio, L. I.; Coats, R. S.; Jennings, C. A.; Sinars, D. B.; Vesey, R. A.; Jones, B.; Ampleford, D. J.; Lemke, R. W.; Martin, M. R.; Schrafel, P. C.; Lewis, S. A.; Moore, J. K.; Savage, M. E.; Stygar, W. A.

    2014-12-08

    Presented are voltage measurements taken near the load region on the Z pulsed-power accelerator using an inductive voltage monitor (IVM). Specifically, the IVM was connected to, and thus monitored the voltage at, the bottom level of the accelerator’s vacuum double post-hole convolute. Additional voltage and current measurements were taken at the accelerator’s vacuum-insulator stack (at a radius of 1.6 m) by using standard D-dot and B-dot probes, respectively. During postprocessing, the measurements taken at the stack were translated to the location of the IVM measurements by using a lossless propagation model of the Z accelerator’s magnetically insulated transmission lines (MITLs) and a lumped inductor model of the vacuum post-hole convolute. Across a wide variety of experiments conducted on the Z accelerator, the voltage histories obtained from the IVM and the lossless propagation technique agree well in overall shape and magnitude. However, large-amplitude, high-frequency oscillations are more pronounced in the IVM records. It is unclear whether these larger oscillations represent true voltage oscillations at the convolute or if they are due to noise pickup and/or transit-time effects and other resonant modes in the IVM. Results using a transit-time-correction technique and Fourier analysis support the latter. Regardless of which interpretation is correct, both true voltage oscillations and the excitement of resonant modes could be the result of transient electrical breakdowns in the post-hole convolute, though more information is required to determine definitively if such breakdowns occurred. Despite the larger oscillations in the IVM records, the general agreement found between the lossless propagation results and the results of the IVM shows that large voltages are transmitted efficiently through the MITLs on Z. These results are complementary to previous studies [R.D. McBride et al., Phys. Rev. ST Accel. Beams 13, 120401 (2010)] that

  19. Voltage measurements at the vacuum post-hole convolute of the Z pulsed-power accelerator

    DOE PAGES

    Waisman, E. M.; McBride, R. D.; Cuneo, M. E.; ...

    2014-12-08

    Presented are voltage measurements taken near the load region on the Z pulsed-power accelerator using an inductive voltage monitor (IVM). Specifically, the IVM was connected to, and thus monitored the voltage at, the bottom level of the accelerator’s vacuum double post-hole convolute. Additional voltage and current measurements were taken at the accelerator’s vacuum-insulator stack (at a radius of 1.6 m) by using standard D-dot and B-dot probes, respectively. During postprocessing, the measurements taken at the stack were translated to the location of the IVM measurements by using a lossless propagation model of the Z accelerator’s magnetically insulated transmission lines (MITLs)more » and a lumped inductor model of the vacuum post-hole convolute. Across a wide variety of experiments conducted on the Z accelerator, the voltage histories obtained from the IVM and the lossless propagation technique agree well in overall shape and magnitude. However, large-amplitude, high-frequency oscillations are more pronounced in the IVM records. It is unclear whether these larger oscillations represent true voltage oscillations at the convolute or if they are due to noise pickup and/or transit-time effects and other resonant modes in the IVM. Results using a transit-time-correction technique and Fourier analysis support the latter. Regardless of which interpretation is correct, both true voltage oscillations and the excitement of resonant modes could be the result of transient electrical breakdowns in the post-hole convolute, though more information is required to determine definitively if such breakdowns occurred. Despite the larger oscillations in the IVM records, the general agreement found between the lossless propagation results and the results of the IVM shows that large voltages are transmitted efficiently through the MITLs on Z. These results are complementary to previous studies [R.D. McBride et al., Phys. Rev. ST Accel. Beams 13, 120401 (2010)] that showed

  20. Voltage measurements at the vacuum post-hole convolute of the Z pulsed-power accelerator

    NASA Astrophysics Data System (ADS)

    Waisman, E. M.; McBride, R. D.; Cuneo, M. E.; Wenger, D. F.; Fowler, W. E.; Johnson, W. A.; Basilio, L. I.; Coats, R. S.; Jennings, C. A.; Sinars, D. B.; Vesey, R. A.; Jones, B.; Ampleford, D. J.; Lemke, R. W.; Martin, M. R.; Schrafel, P. C.; Lewis, S. A.; Moore, J. K.; Savage, M. E.; Stygar, W. A.

    2014-12-01

    Presented are voltage measurements taken near the load region on the Z pulsed-power accelerator using an inductive voltage monitor (IVM). Specifically, the IVM was connected to, and thus monitored the voltage at, the bottom level of the accelerator's vacuum double post-hole convolute. Additional voltage and current measurements were taken at the accelerator's vacuum-insulator stack (at a radius of 1.6 m) by using standard D -dot and B -dot probes, respectively. During postprocessing, the measurements taken at the stack were translated to the location of the IVM measurements by using a lossless propagation model of the Z accelerator's magnetically insulated transmission lines (MITLs) and a lumped inductor model of the vacuum post-hole convolute. Across a wide variety of experiments conducted on the Z accelerator, the voltage histories obtained from the IVM and the lossless propagation technique agree well in overall shape and magnitude. However, large-amplitude, high-frequency oscillations are more pronounced in the IVM records. It is unclear whether these larger oscillations represent true voltage oscillations at the convolute or if they are due to noise pickup and/or transit-time effects and other resonant modes in the IVM. Results using a transit-time-correction technique and Fourier analysis support the latter. Regardless of which interpretation is correct, both true voltage oscillations and the excitement of resonant modes could be the result of transient electrical breakdowns in the post-hole convolute, though more information is required to determine definitively if such breakdowns occurred. Despite the larger oscillations in the IVM records, the general agreement found between the lossless propagation results and the results of the IVM shows that large voltages are transmitted efficiently through the MITLs on Z . These results are complementary to previous studies [R. D. McBride et al., Phys. Rev. ST Accel. Beams 13, 120401 (2010)] that showed efficient

  1. Solvent directed fabrication of Bi{sub 2}WO{sub 6} nanostructures with different morphologies: Synthesis and their shape-dependent photocatalytic properties

    SciTech Connect

    Mi, Yuwei; Zeng, Suyuan; Li, Lei; Zhang, Qingfu; Wang, Suna; Liu, Caihua; Sun, Dezhi

    2012-09-15

    Graphical abstract: The morphologies of the Bi{sub 2}WO{sub 6} nanostructures can be easily tuned by altering the solvent composition during the reaction, which will yield flower-like, pancake-like and tubular nanostructures, respectively. Highlights: ► The morphologies of Bi{sub 2}WO{sub 6} can be controlled by tuning the solvent composition. ► The effects of solvent on the morphologies of Bi{sub 2}WO{sub 6} were carefully investigated. ► The growth mechanisms for the as-prepared samples were investigated. ► The morphologies of the samples greatly affect their photocatalytic activities. -- Abstract: In this work, Bi{sub 2}WO{sub 6} with complex morphologies, namely, flower-like, pancake-like, and tubular shapes have been controllably synthesized by a facile solvothermal process. The as-obtained samples are systematically investigated using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and high resolution transmission electron microscopy (HRTEM). The effects of solvents on the morphologies of Bi{sub 2}WO{sub 6} nanostructures are systematically investigated. According to the time-dependent experiments, a two-step growth mode basing on Ostwald ripening process and self-assembly has been proposed for the formation of the flower-like and pancake-like Bi{sub 2}WO{sub 6} nanostructures. The photocatalytic properties of Bi{sub 2}WO{sub 6} nanostructures are strongly dependent on their shapes, sizes, and structures for the degradation of rhodamine B (RhB) under visible-light irradiation. The deduced reasons for the differences in the photocatalytic activities of these Bi{sub 2}WO{sub 6} nanostructures are further discussed.

  2. Maximum-likelihood estimation of circle parameters via convolution.

    PubMed

    Zelniker, Emanuel E; Clarkson, I Vaughan L

    2006-04-01

    The accurate fitting of a circle to noisy measurements of circumferential points is a much studied problem in the literature. In this paper, we present an interpretation of the maximum-likelihood estimator (MLE) and the Delogne-Kåsa estimator (DKE) for circle-center and radius estimation in terms of convolution on an image which is ideal in a certain sense. We use our convolution-based MLE approach to find good estimates for the parameters of a circle in digital images. In digital images, it is then possible to treat these estimates as preliminary estimates into various other numerical techniques which further refine them to achieve subpixel accuracy. We also investigate the relationship between the convolution of an ideal image with a "phase-coded kernel" (PCK) and the MLE. This is related to the "phase-coded annulus" which was introduced by Atherton and Kerbyson who proposed it as one of a number of new convolution kernels for estimating circle center and radius. We show that the PCK is an approximate MLE (AMLE). We compare our AMLE method to the MLE and the DKE as well as the Cramér-Rao Lower Bound in ideal images and in both real and synthetic digital images.

  3. Hardy's inequalities for the twisted convolution with Laguerre functions.

    PubMed

    Xiao, Jinsen; He, Jianxun

    2017-01-01

    In this article, two types of Hardy's inequalities for the twisted convolution with Laguerre functions are studied. The proofs are mainly based on an estimate for the Heisenberg left-invariant vectors of the special Hermite functions deduced by the Heisenberg group approach.

  4. An Interactive Graphics Program for Assistance in Learning Convolution.

    ERIC Educational Resources Information Center

    Frederick, Dean K.; Waag, Gary L.

    1980-01-01

    A program has been written for the interactive computer graphics facility at Rensselaer Polytechnic Institute that is designed to assist the user in learning the mathematical technique of convolving two functions. Because convolution can be represented graphically by a sequence of steps involving folding, shifting, multiplying, and integration, it…

  5. Stacked Convolutional Denoising Auto-Encoders for Feature Representation.

    PubMed

    Du, Bo; Xiong, Wei; Wu, Jia; Zhang, Lefei; Zhang, Liangpei; Tao, Dacheng

    2016-03-16

    Deep networks have achieved excellent performance in learning representation from visual data. However, the supervised deep models like convolutional neural network require large quantities of labeled data, which are very expensive to obtain. To solve this problem, this paper proposes an unsupervised deep network, called the stacked convolutional denoising auto-encoders, which can map images to hierarchical representations without any label information. The network, optimized by layer-wise training, is constructed by stacking layers of denoising auto-encoders in a convolutional way. In each layer, high dimensional feature maps are generated by convolving features of the lower layer with kernels learned by a denoising auto-encoder. The auto-encoder is trained on patches extracted from feature maps in the lower layer to learn robust feature detectors. To better train the large network, a layer-wise whitening technique is introduced into the model. Before each convolutional layer, a whitening layer is embedded to sphere the input data. By layers of mapping, raw images are transformed into high-level feature representations which would boost the performance of the subsequent support vector machine classifier. The proposed algorithm is evaluated by extensive experimentations and demonstrates superior classification performance to state-of-the-art unsupervised networks.

  6. Inhomogeneous distribution of Alzheimer pathology along the isocortical relief. Are cortical convolutions an Achilles heel of evolution?

    PubMed

    Arendt, Thomas; Morawski, Markus; Gärtner, Ulrich; Fröhlich, Nadine; Schulze, Falko; Wohmann, Nils; Jäger, Carsten; Eisenlöffel, Christian; Gertz, Hermann-Josef; Mueller, Wolf; Brauer, Kurt

    2017-09-01

    Alzheimer's disease (AD) is neuropathologically characterized by neuritic plaques and neurofibrillary tangles. Progression of both plaques and tangles throughout the brain follows a hierarchical distribution which is defined by intrinsic cytoarchitectonic features and extrinsic connectivity patterns. What has less well been studied is how cortical convolutions influence the distribution of AD pathology. Here, the distribution of both plaques and tangles within subsulcal gyral components (fundi) to components forming their top regions at the subarachnoidal brain surface (crowns) by stereological methods in seven different cortical areas was systematically compared. Further, principle differences in cytoarchitectonic organization of cortical crowns and fundi that might provide the background for regionally selective vulnerability were attempted to identify. It was shown that both plaques and tangles were more prominent in sulcal fundi than gyri crowns. The differential distribution of pathology along convolutions corresponds to subgyral differences in the vascular network, GFAP-positive astrocytes and intracortical and subcortical connectivity. While the precise mechanisms accounting for these differences remain open, the presence of systematic inhomogeneities in the distribution of AD pathology along cortical convolutions indicates that the phylogenetic shaping of the cortex is associated with features that render the human brain vulnerable to AD pathology. © 2016 International Society of Neuropathology.

  7. FAST PIXEL SPACE CONVOLUTION FOR COSMIC MICROWAVE BACKGROUND SURVEYS WITH ASYMMETRIC BEAMS AND COMPLEX SCAN STRATEGIES: FEBeCoP

    SciTech Connect

    Mitra, S.; Rocha, G.; Gorski, K. M.; Lawrence, C. R.; Huffenberger, K. M.; Eriksen, H. K.; Ashdown, M. A. J. E-mail: graca@caltech.edu E-mail: Charles.R.Lawrence@jpl.nasa.gov E-mail: h.k.k.eriksen@astro.uio.no

    2011-03-15

    Precise measurement of the angular power spectrum of the cosmic microwave background (CMB) temperature and polarization anisotropy can tightly constrain many cosmological models and parameters. However, accurate measurements can only be realized in practice provided all major systematic effects have been taken into account. Beam asymmetry, coupled with the scan strategy, is a major source of systematic error in scanning CMB experiments such as Planck, the focus of our current interest. We envision Monte Carlo methods to rigorously study and account for the systematic effect of beams in CMB analysis. Toward that goal, we have developed a fast pixel space convolution method that can simulate sky maps observed by a scanning instrument, taking into account real beam shapes and scan strategy. The essence is to pre-compute the 'effective beams' using a computer code, 'Fast Effective Beam Convolution in Pixel space' (FEBeCoP), that we have developed for the Planck mission. The code computes effective beams given the focal plane beam characteristics of the Planck instrument and the full history of actual satellite pointing, and performs very fast convolution of sky signals using the effective beams. In this paper, we describe the algorithm and the computational scheme that has been implemented. We also outline a few applications of the effective beams in the precision analysis of Planck data, for characterizing the CMB anisotropy and for detecting and measuring properties of point sources.

  8. Design and fabrication of a bending rotation fatigue test rig for in situ electrochemical analysis during fatigue testing of NiTi shape memory alloy wires.

    PubMed

    Neelakantan, Lakshman; Zglinski, Jenni Kristin; Frotscher, Matthias; Eggeler, Gunther

    2013-03-01

    The current investigation proposes a novel method for simultaneous assessment of the electrochemical and structural fatigue properties of nickel-titanium shape memory alloy (NiTi SMA) wires. The design and layout of an in situ electrochemical cell in a custom-made bending rotation fatigue (BRF) test rig is presented. This newly designed test rig allows performing a wide spectrum of experiments for studying the influence of fatigue on corrosion and vice versa. This can be achieved by performing ex situ and∕or in situ measurements. The versatility of the combined electrochemical∕mechanical test rig is demonstrated by studying the electrochemical behavior of NiTi SMA wires in 0.9% NaCl electrolyte under load. The ex situ measurements allow addressing various issues, for example, the influence of pre-fatigue on the localized corrosion resistance, or the influence of hydrogen on fatigue life. Ex situ experiments showed that a pre-fatigued wire is more susceptible to localized corrosion. The synergetic effect can be concluded from the polarization studies and specifically from an in situ study of the open circuit potential (OCP) transients, which sensitively react to the elementary repassivation events related to the local failure of the oxide layer. It can also be used as an indicator for identifying the onset of the fatigue failure.

  9. Fabrication of 3D lawn-shaped N-doped porous carbon matrix/polyaniline nanocomposite as the electrode material for supercapacitors

    NASA Astrophysics Data System (ADS)

    Zhang, Xiuling; Ma, Li; Gan, Mengyu; Fu, Gang; Jin, Meng; Lei, Yao; Yang, Peishu; Yan, Maofa

    2017-02-01

    A facile approach to acquire electrode materials with prominent electrochemical property is pivotal to the progress of supercapacitors. 3D nitrogen-doped porous carbon matrix (PCM), with high specific surface area (SSA) up to 2720 m2 g-1, was obtained from the carbonization and activation of the nitrogen-enriched composite precursor (graphene/polyaniline). Then 3D lawn-shaped PCM/PANI composite was obtained by the simple in-situ polymerization. The morphology and structure of these resulting composites were characterized by combining SEM and TEM measurements, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) spectroscopy analyses and Raman spectroscope. The element content of all samples was evaluated using CHN analysis. The results of electrochemical testing indicated that the PCM/PANI composite displays a higher capacitance value of 527 F g-1 at 1 A g-1 compared to 338 F g-1 for pure PANI, and exhibits appreciable rate capability with a retention of 76% at 20 A g-1 as well as fine long-term cycling performance (with 88% retention of specific capacitance after 1000 cycles at 10 A g-1). Simultaneously, the excellent capacitance performance coupled with the facile synthesis of PCM/PANI indicates it is a promising electrode material for supercapacitors.

  10. Design and fabrication of a bending rotation fatigue test rig for in situ electrochemical analysis during fatigue testing of NiTi shape memory alloy wires

    SciTech Connect

    Neelakantan, Lakshman; Zglinski, Jenni Kristin; Eggeler, Gunther; Frotscher, Matthias

    2013-03-15

    The current investigation proposes a novel method for simultaneous assessment of the electrochemical and structural fatigue properties of nickel-titanium shape memory alloy (NiTi SMA) wires. The design and layout of an in situ electrochemical cell in a custom-made bending rotation fatigue (BRF) test rig is presented. This newly designed test rig allows performing a wide spectrum of experiments for studying the influence of fatigue on corrosion and vice versa. This can be achieved by performing ex situ and/or in situ measurements. The versatility of the combined electrochemical/mechanical test rig is demonstrated by studying the electrochemical behavior of NiTi SMA wires in 0.9% NaCl electrolyte under load. The ex situ measurements allow addressing various issues, for example, the influence of pre-fatigue on the localized corrosion resistance, or the influence of hydrogen on fatigue life. Ex situ experiments showed that a pre-fatigued wire is more susceptible to localized corrosion. The synergetic effect can be concluded from the polarization studies and specifically from an in situ study of the open circuit potential (OCP) transients, which sensitively react to the elementary repassivation events related to the local failure of the oxide layer. It can also be used as an indicator for identifying the onset of the fatigue failure.

  11. Segmenting delaminations in carbon fiber reinforced polymer composite CT using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Sammons, Daniel; Winfree, William P.; Burke, Eric; Ji, Shuiwang

    2016-02-01

    Nondestructive evaluation (NDE) utilizes a variety of techniques to inspect various materials for defects without causing changes to the material. X-ray computed tomography (CT) produces large volumes of three dimensional image data. Using the task of identifying delaminations in carbon fiber reinforced polymer (CFRP) composite CT, this work shows that it is possible to automate the analysis of these large volumes of CT data using a machine learning model known as a convolutional neural network (CNN). Further, tests on simulated data sets show that with a robust set of experimental data, it may be possible to go beyond just identification and instead accurately characterize the size and shape of the delaminations with CNNs.

  12. Fast convolution method and its application in mask optimization for intensity calculation using basis expansion.

    PubMed

    Sun, Yaping; Zhang, Jinyu; Wang, Yan; Yu, Zhiping

    2014-12-01

    Finer grid representation is required for a more accurate description of mask patterns in inverse lithography techniques, thus resulting in a large-size mask representation and heavy computational cost. To mitigate the computation problem caused by intensive convolutions in mask optimization, a new method called convolution using basis expansion (CBE) is discussed in this paper. Matrices defined in fine grid are projected on coarse gird under a base matrix set. The new matrices formed by the expansion coefficients are used to perform convolution on the coarse grid. The convolution on fine grid can be approximated by the sum of a few convolutions on coarse grid following an interpolation procedure. The CBE is verified by random matrix convolutions and intensity calculation in lithography simulation. Results show that the use of the CBE method results in similar image quality with significant running speed enhancement compared with traditional convolution method.

  13. Method and apparatus for decoding compatible convolutional codes

    NASA Technical Reports Server (NTRS)

    Doland, G. D. (Inventor)

    1974-01-01

    This invention relates to learning decoders for decoding compatible convolutional codes. The decoder decodes signals which have been encoded by a convolutional coder and allows performance near the theoretical limit of performance for coded data systems. The decoder includes a sub-bit shift register wherein the received sub-bits are entered after regeneration and shifted in synchronization with a clock signal recovered from the received sub-bit stream. The received sub-bits are processed by a sub-bit decision circuit, entered into a sub-bit shift register, decoded by a decision circuit, entered into a data shift register, and updated to reduce data errors. The bit decision circuit utilizes stored sub-bits and stored data bits to determine subsequent data-bits. Data errors are reduced by using at least one up-date circuit.

  14. Two-dimensional convolute integers for analytical instrumentation

    NASA Technical Reports Server (NTRS)

    Edwards, T. R.

    1982-01-01

    As new analytical instruments and techniques emerge with increased dimensionality, a corresponding need is seen for data processing logic which can appropriately address the data. Two-dimensional measurements reveal enhanced unknown mixture analysis capability as a result of the greater spectral information content over two one-dimensional methods taken separately. It is noted that two-dimensional convolute integers are merely an extension of the work by Savitzky and Golay (1964). It is shown that these low-pass, high-pass and band-pass digital filters are truly two-dimensional and that they can be applied in a manner identical with their one-dimensional counterpart, that is, a weighted nearest-neighbor, moving average with zero phase shifting, convoluted integer (universal number) weighting coefficients.

  15. A new computational decoding complexity measure of convolutional codes

    NASA Astrophysics Data System (ADS)

    Benchimol, Isaac B.; Pimentel, Cecilio; Souza, Richard Demo; Uchôa-Filho, Bartolomeu F.

    2014-12-01

    This paper presents a computational complexity measure of convolutional codes well suitable for software implementations of the Viterbi algorithm (VA) operating with hard decision. We investigate the number of arithmetic operations performed by the decoding process over the conventional and minimal trellis modules. A relation between the complexity measure defined in this work and the one defined by McEliece and Lin is investigated. We also conduct a refined computer search for good convolutional codes (in terms of distance spectrum) with respect to two minimal trellis complexity measures. Finally, the computational cost of implementation of each arithmetic operation is determined in terms of machine cycles taken by its execution using a typical digital signal processor widely used for low-power telecommunications applications.

  16. UFLIC: A Line Integral Convolution Algorithm for Visualizing Unsteady Flows

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Kao, David L.; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    This paper presents an algorithm, UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Using the Line Integral Convolution (LIC) as the underlying method, a new convolution algorithm is proposed that can effectively trace the flow's global features over time. The new algorithm consists of a time-accurate value depositing scheme and a successive feed-forward method. The value depositing scheme accurately models the flow advection, and the successive feed-forward method maintains the coherence between animation frames. Our new algorithm can produce time-accurate, highly coherent flow animations to highlight global features in unsteady flow fields. CFD scientists, for the first time, are able to visualize unsteady surface flows using our algorithm.

  17. The analysis of VERITAS muon images using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Feng, Qi; Lin, Tony T. Y.; VERITAS Collaboration

    2017-06-01

    Imaging atmospheric Cherenkov telescopes (IACTs) are sensitive to rare gamma-ray photons, buried in the background of charged cosmic-ray (CR) particles, the flux of which is several orders of magnitude greater. The ability to separate gamma rays from CR particles is important, as it is directly related to the sensitivity of the instrument. This gamma-ray/CR-particle classification problem in IACT data analysis can be treated with the rapidly-advancing machine learning algorithms, which have the potential to outperform the traditional box-cut methods on image parameters. We present preliminary results of a precise classification of a small set of muon events using a convolutional neural networks model with the raw images as input features. We also show the possibility of using the convolutional neural networks model for regression problems, such as the radius and brightness measurement of muon events, which can be used to calibrate the throughput efficiency of IACTs.

  18. Self-Taught convolutional neural networks for short text clustering.

    PubMed

    Xu, Jiaming; Xu, Bo; Wang, Peng; Zheng, Suncong; Tian, Guanhua; Zhao, Jun; Xu, Bo

    2017-04-01

    Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC(2)), which can flexibly and successfully incorporate more useful semantic features and learn non-biased deep text representation in an unsupervised manner. In our framework, the original raw text features are firstly embedded into compact binary codes by using one existing unsupervised dimensionality reduction method. Then, word embeddings are explored and fed into convolutional neural networks to learn deep feature representations, meanwhile the output units are used to fit the pre-trained binary codes in the training process. Finally, we get the optimal clusters by employing K-means to cluster the learned representations. Extensive experimental results demonstrate that the proposed framework is effective, flexible and outperform several popular clustering methods when tested on three public short text datasets.

  19. Deep learning for steganalysis via convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Qian, Yinlong; Dong, Jing; Wang, Wei; Tan, Tieniu

    2015-03-01

    Current work on steganalysis for digital images is focused on the construction of complex handcrafted features. This paper proposes a new paradigm for steganalysis to learn features automatically via deep learning models. We novelly propose a customized Convolutional Neural Network for steganalysis. The proposed model can capture the complex dependencies that are useful for steganalysis. Compared with existing schemes, this model can automatically learn feature representations with several convolutional layers. The feature extraction and classification steps are unified under a single architecture, which means the guidance of classification can be used during the feature extraction step. We demonstrate the effectiveness of the proposed model on three state-of-theart spatial domain steganographic algorithms - HUGO, WOW, and S-UNIWARD. Compared to the Spatial Rich Model (SRM), our model achieves comparable performance on BOSSbase and the realistic and large ImageNet database.

  20. Spectral density of generalized Wishart matrices and free multiplicative convolution

    NASA Astrophysics Data System (ADS)

    Młotkowski, Wojciech; Nowak, Maciej A.; Penson, Karol A.; Życzkowski, Karol

    2015-07-01

    We investigate the level density for several ensembles of positive random matrices of a Wishart-like structure, W =X X† , where X stands for a non-Hermitian random matrix. In particular, making use of the Cauchy transform, we study the free multiplicative powers of the Marchenko-Pastur (MP) distribution, MP⊠s, which for an integer s yield Fuss-Catalan distributions corresponding to a product of s -independent square random matrices, X =X1⋯Xs . New formulas for the level densities are derived for s =3 and s =1 /3 . Moreover, the level density corresponding to the generalized Bures distribution, given by the free convolution of arcsine and MP distributions, is obtained. We also explain the reason of such a curious convolution. The technique proposed here allows for the derivation of the level densities for several other cases.

  1. Rationale-Augmented Convolutional Neural Networks for Text Classification

    PubMed Central

    Zhang, Ye; Marshall, Iain; Wallace, Byron C.

    2016-01-01

    We present a new Convolutional Neural Network (CNN) model for text classification that jointly exploits labels on documents and their constituent sentences. Specifically, we consider scenarios in which annotators explicitly mark sentences (or snippets) that support their overall document categorization, i.e., they provide rationales. Our model exploits such supervision via a hierarchical approach in which each document is represented by a linear combination of the vector representations of its component sentences. We propose a sentence-level convolutional model that estimates the probability that a given sentence is a rationale, and we then scale the contribution of each sentence to the aggregate document representation in proportion to these estimates. Experiments on five classification datasets that have document labels and associated rationales demonstrate that our approach consistently outperforms strong baselines. Moreover, our model naturally provides explanations for its predictions. PMID:28191551

  2. Statistical Downscaling using Super Resolution Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Vandal, T.; Ganguly, S.; Ganguly, A. R.; Kodra, E.

    2016-12-01

    We present a novel approach to statistical downscaling using image super-resolution and convolutional neural networks. Image super-resolution (SR), a widely researched topic in the machine learning community, aims to increase the resolution of low resolution images, similar to the goal of downscaling Global Circulation Models (GCMs). With SR we are able to capture and generalize spatial patterns in the climate by representing each climate state as an "image". In particular, we show the applicability of Super Resolution Convolutional Neural Networks (SRCNN) to downscaling daily precipitation in the United States. SRCNN is a state-of-the-art single image SR method and has the advantage of utilizing multiple input variables, known as channels. We apply SRCNN to downscaling precipitation by using low resolution precipitation and high resolution elevation as inputs and compare to bias correction spatial disaggregation (BCSD).

  3. Fully convolutional neural networks for polyp segmentation in colonoscopy

    NASA Astrophysics Data System (ADS)

    Brandao, Patrick; Mazomenos, Evangelos; Ciuti, Gastone; Caliò, Renato; Bianchi, Federico; Menciassi, Arianna; Dario, Paolo; Koulaouzidis, Anastasios; Arezzo, Alberto; Stoyanov, Danail

    2017-03-01

    Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer, accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is considered the most effective method for screening and diagnosis, the success of the procedure is highly dependent on the operator skills and level of hand-eye coordination. In this work, we propose to adapt fully convolution neural networks (FCN), to identify and segment polyps in colonoscopy images. We converted three established networks into a fully convolution architecture and fine-tuned their learned representations to the polyp segmentation task. We validate our framework on the 2015 MICCAI polyp detection challenge dataset, surpassing the state-of-the-art in automated polyp detection. Our method obtained high segmentation accuracy and a detection precision and recall of 73.61% and 86.31%, respectively.

  4. Spectral density of generalized Wishart matrices and free multiplicative convolution.

    PubMed

    Młotkowski, Wojciech; Nowak, Maciej A; Penson, Karol A; Życzkowski, Karol

    2015-07-01

    We investigate the level density for several ensembles of positive random matrices of a Wishart-like structure, W=XX(†), where X stands for a non-Hermitian random matrix. In particular, making use of the Cauchy transform, we study the free multiplicative powers of the Marchenko-Pastur (MP) distribution, MP(⊠s), which for an integer s yield Fuss-Catalan distributions corresponding to a product of s-independent square random matrices, X=X(1)⋯X(s). New formulas for the level densities are derived for s=3 and s=1/3. Moreover, the level density corresponding to the generalized Bures distribution, given by the free convolution of arcsine and MP distributions, is obtained. We also explain the reason of such a curious convolution. The technique proposed here allows for the derivation of the level densities for several other cases.

  5. UFLIC: A Line Integral Convolution Algorithm for Visualizing Unsteady Flows

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Kao, David L.; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    This paper presents an algorithm, UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Using the Line Integral Convolution (LIC) as the underlying method, a new convolution algorithm is proposed that can effectively trace the flow's global features over time. The new algorithm consists of a time-accurate value depositing scheme and a successive feed-forward method. The value depositing scheme accurately models the flow advection, and the successive feed-forward method maintains the coherence between animation frames. Our new algorithm can produce time-accurate, highly coherent flow animations to highlight global features in unsteady flow fields. CFD scientists, for the first time, are able to visualize unsteady surface flows using our algorithm.

  6. Image interpolation by two-dimensional parametric cubic convolution.

    PubMed

    Shi, Jiazheng; Reichenbach, Stephen E

    2006-07-01

    Cubic convolution is a popular method for image interpolation. Traditionally, the piecewise-cubic kernel has been derived in one dimension with one parameter and applied to two-dimensional (2-D) images in a separable fashion. However, images typically are statistically nonseparable, which motivates this investigation of nonseparable cubic convolution. This paper derives two new nonseparable, 2-D cubic-convolution kernels. The first kernel, with three parameters (designated 2D-3PCC), is the most general 2-D, piecewise-cubic interpolator defined on [-2, 2] x [-2, 2] with constraints for biaxial symmetry, diagonal (or 90 degrees rotational) symmetry, continuity, and smoothness. The second kernel, with five parameters (designated 2D-5PCC), relaxes the constraint of diagonal symmetry, based on the observation that many images have rotationally asymmetric statistical properties. This paper also develops a closed-form solution for determining the optimal parameter values for parametric cubic-convolution kernels with respect to ensembles of scenes characterized by autocorrelation (or power spectrum). This solution establishes a practical foundation for adaptive interpolation based on local autocorrelation estimates. Quantitative fidelity analyses and visual experiments indicate that these new methods can outperform several popular interpolation methods. An analysis of the error budgets for reconstruction error associated with blurring and aliasing illustrates that the methods improve interpolation fidelity for images with aliased components. For images with little or no aliasing, the methods yield results similar to other popular methods. Both 2D-3PCC and 2D-5PCC are low-order polynomials with small spatial support and so are easy to implement and efficient to apply.

  7. New syndrome decoder for (n, 1) convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1983-01-01

    The letter presents a new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck. The new technique uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). A recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector E(D). An example is given for the binary nonsystematic (2, 1) CC.

  8. Convolution using guided acoustooptical interaction in thin-film waveguides

    NASA Technical Reports Server (NTRS)

    Chang, W. S. C.; Becker, R. A.; Tsai, C. S.; Yao, I. W.

    1977-01-01

    Interaction of two antiparallel acoustic surface waves (ASW) with an optical guided wave has been investigated theoretically as well as experimentally to obtain the convolution of two ASW signals. The maximum time-bandwidth product that can be achieved by such a convolver is shown to be of the order of 1000 or more. The maximum dynamic range can be as large as 83 dB.

  9. Image data compression using cubic convolution spline interpolation.

    PubMed

    Truong, T K; Wang, L J; Reed, I S; Hsieh, W S

    2000-01-01

    A new cubic convolution spline interpolation (CCSI )for both one-dimensional (1-D) and two-dimensional (2-D) signals is developed in order to subsample signal and image compression data. The CCSI yields a very accurate algorithm for smoothing. It is also shown that this new and fast smoothing filter for CCSI can be used with the JPEG standard to design an improved JPEG encoder-decoder for a high compression ratio.

  10. Automatic localization of vertebrae based on convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Shen, Wei; Yang, Feng; Mu, Wei; Yang, Caiyun; Yang, Xin; Tian, Jie

    2015-03-01

    Localization of the vertebrae is of importance in many medical applications. For example, the vertebrae can serve as the landmarks in image registration. They can also provide a reference coordinate system to facilitate the localization of other organs in the chest. In this paper, we propose a new vertebrae localization method using convolutional neural networks (CNN). The main advantage of the proposed method is the removal of hand-crafted features. We construct two training sets to train two CNNs that share the same architecture. One is used to distinguish the vertebrae from other tissues in the chest, and the other is aimed at detecting the centers of the vertebrae. The architecture contains two convolutional layers, both of which are followed by a max-pooling layer. Then the output feature vector from the maxpooling layer is fed into a multilayer perceptron (MLP) classifier which has one hidden layer. Experiments were performed on ten chest CT images. We used leave-one-out strategy to train and test the proposed method. Quantitative comparison between the predict centers and ground truth shows that our convolutional neural networks can achieve promising localization accuracy without hand-crafted features.

  11. A model of traffic signs recognition with convolutional neural network

    NASA Astrophysics Data System (ADS)

    Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

    2016-10-01

    In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.

  12. Fine-grained representation learning in convolutional autoencoders

    NASA Astrophysics Data System (ADS)

    Luo, Chang; Wang, Jie

    2016-03-01

    Convolutional autoencoders (CAEs) have been widely used as unsupervised feature extractors for high-resolution images. As a key component in CAEs, pooling is a biologically inspired operation to achieve scale and shift invariances, and the pooled representation directly affects the CAEs' performance. Fine-grained pooling, which uses small and dense pooling regions, encodes fine-grained visual cues and enhances local characteristics. However, it tends to be sensitive to spatial rearrangements. In most previous works, pooled features were obtained by empirically modulating parameters in CAEs. We see the CAE as a whole and propose a fine-grained representation learning law to extract better fine-grained features. This representation learning law suggests two directions for improvement. First, we probabilistically evaluate the discrimination-invariance tradeoff with fine-grained granularity in the pooled feature maps, and suggest the proper filter scale in the convolutional layer and appropriate whitening parameters in preprocessing step. Second, pooling approaches are combined with the sparsity degree in pooling regions, and we propose the preferable pooling approach. Experimental results on two independent benchmark datasets demonstrate that our representation learning law could guide CAEs to extract better fine-grained features and performs better in multiclass classification task. This paper also provides guidance for selecting appropriate parameters to obtain better fine-grained representation in other convolutional neural networks.

  13. Fast convolution quadrature for the wave equation in three dimensions

    NASA Astrophysics Data System (ADS)

    Banjai, L.; Kachanovska, M.

    2014-12-01

    This work addresses the numerical solution of time-domain boundary integral equations arising from acoustic and electromagnetic scattering in three dimensions. The semidiscretization of the time-domain boundary integral equations by Runge-Kutta convolution quadrature leads to a lower triangular Toeplitz system of size N. This system can be solved recursively in an almost linear time (O(Nlog2⁡N)), but requires the construction of O(N) dense spatial discretizations of the single layer boundary operator for the Helmholtz equation. This work introduces an improvement of this algorithm that allows to solve the scattering problem in an almost linear time. The new approach is based on two main ingredients: the near-field reuse and the application of data-sparse techniques. Exponential decay of Runge-Kutta convolution weights wnh(d) outside of a neighborhood of d≈nh (where h is a time step) allows to avoid constructing the near-field (i.e. singular and near-singular integrals) for most of the discretizations of the single layer boundary operators (near-field reuse). The far-field of these matrices is compressed with the help of data-sparse techniques, namely, H-matrices and the high-frequency fast multipole method. Numerical experiments indicate the efficiency of the proposed approach compared to the conventional Runge-Kutta convolution quadrature algorithm.

  14. Deep Convolutional Neural Network for Inverse Problems in Imaging

    NASA Astrophysics Data System (ADS)

    Jin, Kyong Hwan; McCann, Michael T.; Froustey, Emmanuel; Unser, Michael

    2017-09-01

    In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. These methods produce excellent results, but can be challenging to deploy in practice due to factors including the high computational cost of the forward and adjoint operators and the difficulty of hyper parameter selection. The starting point of our work is the observation that unrolled iterative methods have the form of a CNN (filtering followed by point-wise non-linearity) when the normal operator (H*H, the adjoint of H times H) of the forward model is a convolution. Based on this observation, we propose using direct inversion followed by a CNN to solve normal-convolutional inverse problems. The direct inversion encapsulates the physical model of the system, but leads to artifacts when the problem is ill-posed; the CNN combines multiresolution decomposition and residual learning in order to learn to remove these artifacts while preserving image structure. We demonstrate the performance of the proposed network in sparse-view reconstruction (down to 50 views) on parallel beam X-ray computed tomography in synthetic phantoms as well as in real experimental sinograms. The proposed network outperforms total variation-regularized iterative reconstruction for the more realistic phantoms and requires less than a second to reconstruct a 512 x 512 image on GPU.

  15. Calcium transport in the rabbit superficial proximal convoluted tubule

    SciTech Connect

    Ng, R.C.; Rouse, D.; Suki, W.N.

    1984-09-01

    Calcium transport was studied in isolated S2 segments of rabbit superficial proximal convoluted tubules. 45Ca was added to the perfusate for measurement of lumen-to-bath flux (JlbCa), to the bath for bath-to-lumen flux (JblCa), and to both perfusate and bath for net flux (JnetCa). In these studies, the perfusate consisted of an equilibrium solution that was designed to minimize water flux or electrochemical potential differences (PD). Under these conditions, JlbCa (9.1 +/- 1.0 peq/mm X min) was not different from JblCa (7.3 +/- 1.3 peq/mm X min), and JnetCa was not different from zero, which suggests that calcium transport in the superficial proximal convoluted tubule is due primarily to passive transport. The efflux coefficient was 9.5 +/- 1.2 X 10(-5) cm/s, which was not significantly different from the influx coefficient, 7.0 +/- 1.3 X 10(-5) cm/s. When the PD was made positive or negative with use of different perfusates, net calcium absorption or secretion was demonstrated, respectively, which supports a major role for passive transport. These results indicate that in the superficial proximal convoluted tubule of the rabbit, passive driving forces are the major determinants of calcium transport.

  16. Robust hepatic vessel segmentation using multi deep convolution network

    NASA Astrophysics Data System (ADS)

    Kitrungrotsakul, Titinunt; Han, Xian-Hua; Iwamoto, Yutaro; Foruzan, Amir Hossein; Lin, Lanfen; Chen, Yen-Wei

    2017-03-01

    Extraction of blood vessels of the organ is a challenging task in the area of medical image processing. It is really difficult to get accurate vessel segmentation results even with manually labeling by human being. The difficulty of vessels segmentation is the complicated structure of blood vessels and its large variations that make them hard to recognize. In this paper, we present deep artificial neural network architecture to automatically segment the hepatic vessels from computed tomography (CT) image. We proposed novel deep neural network (DNN) architecture for vessel segmentation from a medical CT volume, which consists of three deep convolution neural networks to extract features from difference planes of CT data. The three networks have share features at the first convolution layer but will separately learn their own features in the second layer. All three networks will join again at the top layer. To validate effectiveness and efficiency of our proposed method, we conduct experiments on 12 CT volumes which training data are randomly generate from 5 CT volumes and 7 using for test. Our network can yield an average dice coefficient 0.830, while 3D deep convolution neural network can yield around 0.7 and multi-scale can yield only 0.6.

  17. Novel WSi/Au T-shaped gate GaAs metal-semiconductor field-effect-transistor fabrication process for super low-noise microwave monolithic integrated circuit amplifiers

    SciTech Connect

    Takano, H.; Hosogi, K.; Kato, T.

    1995-05-01

    A fully ion-implanted self-aligned T-shaped gate Ga As metal-semiconductor field-effect transistor (MESFET) with high frequency and extremely low-noise performance has been successfully fabricated for super low-noise microwave monolithic integrated circuit (MMIC) amplifiers. A subhalf-micrometer gate structure composed of WSi/Ti/Mo/Au is employed to reduce gate resistance effectively. This multilayer gate structure is formed by newly developed dummy SiON self-alignment technology and a photoresist planarization process. At an operating frequency of 12 GHz, a minimum noise figure of 0.87 dB with an associated gain of 10.62 dB has been obtained. Based on the novel FET process, a low-noise single-stage MMIC amplifier with an excellent low-noise figure of 1.2 dB with an associated gain of 8 dB in the 14 GHz band has been realized. This is the lowest noise figure ever reported at this frequency for low-noise MMICs based on ion-implanted self-aligned gate MESFET technology. 14 refs., 9 figs.

  18. Mechanics of a Knitted Fabric

    NASA Astrophysics Data System (ADS)

    Poincloux, Samuel; Lechenault, Frederic; Adda-Bedia, Mokhtar

    A simple knitted fabric can be seen as a topologically constrained slender rod following a periodic path. The non-linear properties of the fabric, such as large reversible deformation and characteristic shape under stress, arise from topological features known as stitches and are distinct from the constitutive yarn properties. Through experiments we studied a model stockinette fabric made of a single elastic thread, where the mechanical properties and local stitch displacements were measured. Then, we derived a model based on the yarn bending energy at the stitch level resulting in an evaluation of the displacement fields of the repetitive units which describe the fabric shape. The comparison between the predicted and the measured shape gives very good agreement and the right order of magnitude for the mechanical response is captured. This work aims at providing a fundamental framework for the understanding of knitted systems, paving the way to thread based smart materials. Contract ANR-14-CE07-0031-01 METAMAT.

  19. In Situ Fabrication Technologies

    NASA Technical Reports Server (NTRS)

    Rolin, Terry D.; Hammond, Monica

    2005-01-01

    A manufacturing system is described that is internal to controlled cabin environments which will produce functional parts to net shape with sufficient tolerance, strength and integrity to meet application specific needs such as CEV ECLS components, robotic arm or rover components, EVA suit items, unforeseen tools, conformal repair patches, and habitat fittings among others. Except for start-up and shut-down, fabrication will be automatic without crew intervention under nominal scenarios. Off-nominal scenarios may require crew and/or Earth control intervention. System will have the ability to fabricate using both provisioned feedstock materials and feedstock refined from in situ regolith.

  20. Super-resolution reconstruction algorithm based on adaptive convolution kernel size selection

    NASA Astrophysics Data System (ADS)

    Gao, Hang; Chen, Qian; Sui, Xiubao; Zeng, Junjie; Zhao, Yao

    2016-09-01

    Restricted by the detector technology and optical diffraction limit, the spatial resolution of infrared imaging system is difficult to achieve significant improvement. Super-Resolution (SR) reconstruction algorithm is an effective way to solve this problem. Among them, the SR algorithm based on multichannel blind deconvolution (MBD) estimates the convolution kernel only by low resolution observation images, according to the appropriate regularization constraints introduced by a priori assumption, to realize the high resolution image restoration. The algorithm has been shown effective when each channel is prime. In this paper, we use the significant edges to estimate the convolution kernel and introduce an adaptive convolution kernel size selection mechanism, according to the uncertainty of the convolution kernel size in MBD processing. To reduce the interference of noise, we amend the convolution kernel in an iterative process, and finally restore a clear image. Experimental results show that the algorithm can meet the convergence requirement of the convolution kernel estimation.

  1. Improved iterative image reconstruction using variable projection binning and abbreviated convolution.

    PubMed

    Schmidlin, P

    1994-09-01

    Noise propagation in iterative reconstruction can be reduced by exact data projection. This can be done by area-weighted projection using the convolution method. Large arrays have to be convolved in order to achieve satisfactory image quality. Two procedures are described which improve the convolution method used so far. Variable binning helps to reduce the size of the convolution arrays without loss of image quality. Computation time is further reduced by abbreviated convolution. The effects of the procedures are illustrated by means of phantom measurements.

  2. Operational and convolution properties of three-dimensional Fourier transforms in spherical polar coordinates.

    PubMed

    Baddour, Natalie

    2010-10-01

    For functions that are best described with spherical coordinates, the three-dimensional Fourier transform can be written in spherical coordinates as a combination of spherical Hankel transforms and spherical harmonic series. However, to be as useful as its Cartesian counterpart, a spherical version of the Fourier operational toolset is required for the standard operations of shift, multiplication, convolution, etc. This paper derives the spherical version of the standard Fourier operation toolset. In particular, convolution in various forms is discussed in detail as this has important consequences for filtering. It is shown that standard multiplication and convolution rules do apply as long as the correct definition of convolution is applied.

  3. Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data

    NASA Astrophysics Data System (ADS)

    Anirudh, Rushil; Thiagarajan, Jayaraman J.; Bremer, Timo; Kim, Hyojin

    2016-03-01

    Early detection of lung nodules is currently the one of the most effective ways to predict and treat lung cancer. As a result, the past decade has seen a lot of focus on computer aided diagnosis (CAD) of lung nodules, whose goal is to efficiently detect, segment lung nodules and classify them as being benign or malignant. Effective detection of such nodules remains a challenge due to their arbitrariness in shape, size and texture. In this paper, we propose to employ 3D convolutional neural networks (CNN) to learn highly discriminative features for nodule detection in lieu of hand-engineered ones such as geometric shape or texture. While 3D CNNs are promising tools to model the spatio-temporal statistics of data, they are limited by their need for detailed 3D labels, which can be prohibitively expensive when compared obtaining 2D labels. Existing CAD methods rely on obtaining detailed labels for lung nodules, to train models, which is also unrealistic and time consuming. To alleviate this challenge, we propose a solution wherein the expert needs to provide only a point label, i.e., the central pixel of of the nodule, and its largest expected size. We use unsupervised segmentation to grow out a 3D region, which is used to train the CNN. Using experiments on the SPIE-LUNGx dataset, we show that the network trained using these weak labels can produce reasonably low false positive rates with a high sensitivity, even in the absence of accurate 3D labels.

  4. Intraocular lens fabrication

    DOEpatents

    Salazar, Mike A.; Foreman, Larry R.

    1997-01-01

    This invention describes a method for fabricating an intraocular lens made rom clear Teflon.TM., Mylar.TM., or other thermoplastic material having a thickness of about 0.025 millimeters. These plastic materials are thermoformable and biocompatable with the human eye. The two shaped lenses are bonded together with a variety of procedures which may include thermosetting and solvent based adhesives, laser and impulse welding, and ultrasonic bonding. The fill tube, which is used to inject a refractive filling material is formed with the lens so as not to damage the lens shape. A hypodermic tube may be included inside the fill tube.

  5. Intraocular lens fabrication

    DOEpatents

    Salazar, M.A.; Foreman, L.R.

    1997-07-08

    This invention describes a method for fabricating an intraocular lens made from clear Teflon{trademark}, Mylar{trademark}, or other thermoplastic material having a thickness of about 0.025 millimeters. These plastic materials are thermoformable and biocompatable with the human eye. The two shaped lenses are bonded together with a variety of procedures which may include thermosetting and solvent based adhesives, laser and impulse welding, and ultrasonic bonding. The fill tube, which is used to inject a refractive filling material is formed with the lens so as not to damage the lens shape. A hypodermic tube may be included inside the fill tube. 13 figs.

  6. Bayesian Vision for Shape Recovery

    NASA Technical Reports Server (NTRS)

    Jalobeanu, Andre

    2004-01-01

    We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.

  7. Bayesian Vision for Shape Recovery

    NASA Astrophysics Data System (ADS)

    Jalobeanu, André

    2004-11-01

    We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The modeled observation process, equivalent to rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function, and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by a hierarchy of approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates of both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.

  8. Finding strong lenses in CFHTLS using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Jacobs, C.; Glazebrook, K.; Collett, T.; More, A.; McCarthy, C.

    2017-10-01

    We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong lensing systems. An ensemble of four convolutional neural networks was trained on images of simulated galaxy-galaxy lenses. The training sets consisted of a total of 62 406 simulated lenses and 64 673 non-lens negative examples generated with two different methodologies. An ensemble of trained networks was applied to all of the 171 deg2 of the CFHTLS wide field image data, identifying 18 861 candidates including 63 known and 139 other potential lens candidates. A second search of 1.4 million early-type galaxies selected from the survey catalogue as potential deflectors, identified 2465 candidates including 117 previously known lens candidates, 29 confirmed lenses/high-quality lens candidates, 266 novel probable or potential lenses and 2097 candidates we classify as false positives. For the catalogue-based search we estimate a completeness of 21-28 per cent with respect to detectable lenses and a purity of 15 per cent, with a false-positive rate of 1 in 671 images tested. We predict a human astronomer reviewing candidates produced by the system would identify 20 probable lenses and 100 possible lenses per hour in a sample selected by the robot. Convolutional neural networks are therefore a promising tool for use in the search for lenses in current and forthcoming surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

  9. Medical image fusion using the convolution of Meridian distributions.

    PubMed

    Agrawal, Mayank; Tsakalides, Panagiotis; Achim, Alin

    2010-01-01

    The aim of this paper is to introduce a novel non-Gaussian statistical model-based approach for medical image fusion based on the Meridian distribution. The paper also includes a new approach to estimate the parameters of generalized Cauchy distribution. The input images are first decomposed using the Dual-Tree Complex Wavelet Transform (DT-CWT) with the subband coefficients modelled as Meridian random variables. Then, the convolution of Meridian distributions is applied as a probabilistic prior to model the fused coefficients, and the weights used to combine the source images are optimised via Maximum Likelihood (ML) estimation. The superior performance of the proposed method is demonstrated using medical images.

  10. Faster GPU-based convolutional gridding via thread coarsening

    NASA Astrophysics Data System (ADS)

    Merry, B.

    2016-07-01

    Convolutional gridding is a processor-intensive step in interferometric imaging. While it is possible to use graphics processing units (GPUs) to accelerate this operation, existing methods use only a fraction of the available flops. We apply thread coarsening to improve the efficiency of an existing algorithm, and observe performance gains of up to 3.2 × for single-polarization gridding and 1.9 × for quad-polarization gridding on a GeForce GTX 980, and smaller but still significant gains on a Radeon R9 290X.

  11. Convolutional neural networks for synthetic aperture radar classification

    NASA Astrophysics Data System (ADS)

    Profeta, Andrew; Rodriguez, Andres; Clouse, H. Scott

    2016-05-01

    For electro-optical object recognition, convolutional neural networks (CNNs) are the state-of-the-art. For large datasets, CNNs are able to learn meaningful features used for classification. However, their application to synthetic aperture radar (SAR) has been limited. In this work we experimented with various CNN architectures on the MSTAR SAR dataset. As the input to the CNN we used the magnitude and phase (2 channels) of the SAR imagery. We used the deep learning toolboxes CAFFE and Torch7. Our results show that we can achieve 93% accuracy on the MSTAR dataset using CNNs.

  12. New syndrome decoding techniques for the (n, k) convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1984-01-01

    This paper presents a new syndrome decoding algorithm for the (n, k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3, 1)CC. Previously announced in STAR as N83-34964

  13. New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1983-01-01

    This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

  14. Simplified Syndrome Decoding of (n, 1) Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1983-01-01

    A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

  15. Surrogacy theory and models of convoluted organic systems.

    PubMed

    Konopka, Andrzej K

    2007-03-01

    The theory of surrogacy is briefly outlined as one of the conceptual foundations of systems biology that has been developed for the last 30 years in the context of Hertz-Rosen modeling relationship. Conceptual foundations of modeling convoluted (biologically complex) systems are briefly reviewed and discussed in terms of current and future research in systems biology. New as well as older results that pertain to the concepts of modeling relationship, sequence of surrogacies, cascade of representations, complementarity, analogy, metaphor, and epistemic time are presented together with a classification of models in a cascade. Examples of anticipated future applications of surrogacy theory in life sciences are briefly discussed.

  16. A Fortran 90 code for magnetohydrodynamics. Part 1, Banded convolution

    SciTech Connect

    Walker, D.W.

    1992-03-01

    This report describes progress in developing a Fortran 90 version of the KITE code for studying plasma instabilities in Tokamaks. In particular, the evaluation of convolution terms appearing in the numerical solution is discussed, and timing results are presented for runs performed on an 8k processor Connection Machine (CM-2). Estimates of the performance on a full-size 64k CM-2 are given, and range between 100 and 200 Mflops. The advantages of having a Fortran 90 version of the KITE code are stressed, and the future use of such a code on the newly announced CM5 and Paragon computers, from Thinking Machines Corporation and Intel, is considered.

  17. Convolution Algebra for Fluid Modes with Finite Energy

    DTIC Science & Technology

    1992-04-01

    PHILLIPS LABORATORY AIR FORCE SYSTEMS COMMAND UNITED STATES AIR FORCE HANSCOM AIR FORCE BASE, MASSACHIUSETTS 01731-5000 94-22604 "This technical report ’-as...with finite spatial and temporal extents. At Boston University, we have developed a full form of wavelet expansion which has the advantage over more...distribution: 00 bX =00 0l if, TZ< VPf (X) = V •a,,,’(x) = E bnb 𔄀(x) where b, =otherwise (34) V=o ,i=o a._, otherwise 7 The convolution of two

  18. Continuous speech recognition based on convolutional neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Qing-qing; Liu, Yong; Pan, Jie-lin; Yan, Yong-hong

    2015-07-01

    Convolutional Neural Networks (CNNs), which showed success in achieving translation invariance for many image processing tasks, are investigated for continuous speech recognitions in the paper. Compared to Deep Neural Networks (DNNs), which have been proven to be successful in many speech recognition tasks nowadays, CNNs can reduce the NN model sizes significantly, and at the same time achieve even better recognition accuracies. Experiments on standard speech corpus TIMIT showed that CNNs outperformed DNNs in the term of the accuracy when CNNs had even smaller model size.

  19. Convolution seal for transition duct in turbine system

    DOEpatents

    Flanagan, James Scott; LeBegue, Jeffrey Scott; McMahan, Kevin Weston; Dillard, Daniel Jackson; Pentecost, Ronnie Ray

    2015-05-26

    A turbine system is disclosed. In one embodiment, the turbine system includes a transition duct. The transition duct includes an inlet, an outlet, and a passage extending between the inlet and the outlet and defining a longitudinal axis, a radial axis, and a tangential axis. The outlet of the transition duct is offset from the inlet along the longitudinal axis and the tangential axis. The transition duct further includes an interface feature for interfacing with an adjacent transition duct. The turbine system further includes a convolution seal contacting the interface feature to provide a seal between the interface feature and the adjacent transition duct.

  20. A digital model for streamflow routing by convolution methods

    USGS Publications Warehouse

    Doyle, W.H.; Shearman, H.O.; Stiltner, G.J.; Krug, W.O.

    1984-01-01

    U.S. Geological Survey computer model, CONROUT, for routing streamflow by unit-response convolution flow-routing techniques from an upstream channel location to a downstream channel location has been developed and documented. Calibration and verification of the flow-routing model and subsequent use of the model for simulation is also documented. Three hypothetical examples and two field applications are presented to illustrate basic flow-routing concepts. Most of the discussion is limited to daily flow routing since, to date, all completed and current studies of this nature involve daily flow routing. However, the model is programmed to accept hourly flow-routing data. (USGS)

  1. Tandem mass spectrometry data quality assessment by self-convolution

    PubMed Central

    Choo, Keng Wah; Tham, Wai Mun

    2007-01-01

    Background Many algorithms have been developed for deciphering the tandem mass spectrometry (MS) data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on de novo sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified. Results The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current) component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores. Conclusion We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the predicted results. We conclude that

  2. Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Johnson, Christopher R.; Ma, Kwan-Liu

    1996-01-01

    We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

  3. Convolution seal for transition duct in turbine system

    DOEpatents

    Flanagan, James Scott; LeBegue, Jeffrey Scott; McMahan, Kevin Weston; Dillard, Daniel Jackson; Pentecost, Ronnie Ray

    2015-03-10

    A turbine system is disclosed. In one embodiment, the turbine system includes a transition duct. The transition duct includes an inlet, an outlet, and a passage extending between the inlet and the outlet and defining a longitudinal axis, a radial axis, and a tangential axis. The outlet of the transition duct is offset from the inlet along the longitudinal axis and the tangential axis. The transition duct further includes an interface member for interfacing with a turbine section. The turbine system further includes a convolution seal contacting the interface member to provide a seal between the interface member and the turbine section.

  4. Fabric fastenings

    NASA Technical Reports Server (NTRS)

    Walen, E D; Fisher, R T

    1920-01-01

    The study of aeronautical fabrics has led to a consideration of the best methods of attaching and fastening together such materials. This report presents the results of an investigation upon the proper methods of attaching fabrics to airplane wings. The methods recommended in this report have been adopted by the military services.

  5. Fast space-varying convolution using matrix source coding with applications to camera stray light reduction.

    PubMed

    Wei, Jianing; Bouman, Charles A; Allebach, Jan P

    2014-05-01

    Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to refer to linear operators whose impulse response has slow spatial variation. In addition, these space-varying convolution operators are often dense, so direct implementation of the convolution operator is typically computationally impractical. One such example is the problem of stray light reduction in digital cameras, which requires the implementation of a dense space-varying deconvolution operator. However, other inverse problems, such as iterative tomographic reconstruction, can also depend on the implementation of dense space-varying convolution. While space-invariant convolution can be efficiently implemented with the fast Fourier transform, this approach does not work for space-varying operators. So direct convolution is often the only option for implementing space-varying convolution. In this paper, we develop a general approach to the efficient implementation of space-varying convolution, and demonstrate its use in the application of stray light reduction. Our approach, which we call matrix source coding, is based on lossy source coding of the dense space-varying convolution matrix. Importantly, by coding the transformation matrix, we not only reduce the memory required to store it; we also dramatically reduce the computation required to implement matrix-vector products. Our algorithm is able to reduce computation by approximately factoring the dense space-varying convolution operator into a product of sparse transforms. Experimental results show that our method can dramatically reduce the computation required for stray light reduction while maintaining high accuracy.

  6. An optimal nonorthogonal separation of the anisotropic Gaussian convolution filter.

    PubMed

    Lampert, Christoph H; Wirjadi, Oliver

    2006-11-01

    We give an analytical and geometrical treatment of what it means to separate a Gaussian kernel along arbitrary axes in R(n), and we present a separation scheme that allows us to efficiently implement anisotropic Gaussian convolution filters for data of arbitrary dimensionality. Based on our previous analysis we show that this scheme is optimal with regard to the number of memory accesses and interpolation operations needed. The proposed method relies on nonorthogonal convolution axes and works completely in image space. Thus, it avoids the need for a fast Fourier transform (FFT)-subroutine. Depending on the accuracy and speed requirements, different interpolation schemes and methods to implement the one-dimensional Gaussian (finite impulse response and infinite impulse response) can be integrated. Special emphasis is put on analyzing the performance and accuracy of the new method. In particular, we show that without any special optimization of the source code, it can perform anisotropic Gaussian filtering faster than methods relying on the FFT.

  7. Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation

    NASA Astrophysics Data System (ADS)

    Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.

    2017-05-01

    Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.

  8. Digital image correlation based on a fast convolution strategy

    NASA Astrophysics Data System (ADS)

    Yuan, Yuan; Zhan, Qin; Xiong, Chunyang; Huang, Jianyong

    2017-10-01

    In recent years, the efficiency of digital image correlation (DIC) methods has attracted increasing attention because of its increasing importance for many engineering applications. Based on the classical affine optical flow (AOF) algorithm and the well-established inverse compositional Gauss-Newton algorithm, which is essentially a natural extension of the AOF algorithm under a nonlinear iterative framework, this paper develops a set of fast convolution-based DIC algorithms for high-efficiency subpixel image registration. Using a well-developed fast convolution technique, the set of algorithms establishes a series of global data tables (GDTs) over the digital images, which allows the reduction of the computational complexity of DIC significantly. Using the pre-calculated GDTs, the subpixel registration calculations can be implemented efficiently in a look-up-table fashion. Both numerical simulation and experimental verification indicate that the set of algorithms significantly enhances the computational efficiency of DIC, especially in the case of a dense data sampling for the digital images. Because the GDTs need to be computed only once, the algorithms are also suitable for efficiently coping with image sequences that record the time-varying dynamics of specimen deformations.

  9. Enhancing Neutron Beam Production with a Convoluted Moderator

    SciTech Connect

    Iverson, Erik B; Baxter, David V; Muhrer, Guenter; Ansell, Stuart; Gallmeier, Franz X; Dalgliesh, Robert; Lu, Wei; Kaiser, Helmut

    2014-10-01

    We describe a new concept for a neutron moderating assembly resulting in the more efficient production of slow neutron beams. The Convoluted Moderator, a heterogeneous stack of interleaved moderating material and nearly transparent single-crystal spacers, is a directionally-enhanced neutron beam source, improving beam effectiveness over an angular range comparable to the range accepted by neutron beam lines and guides. We have demonstrated gains of 50% in slow neutron intensity for a given fast neutron production rate while simultaneously reducing the wavelength-dependent emission time dispersion by 25%, both coming from a geometric effect in which the neutron beam lines view a large surface area of moderating material in a relatively small volume. Additionally, we have confirmed a Bragg-enhancement effect arising from coherent scattering within the single-crystal spacers. We have not observed hypothesized refractive effects leading to additional gains at long wavelength. In addition to confirmation of the validity of the Convoluted Moderator concept, our measurements provide a series of benchmark experiments suitable for developing simulation and analysis techniques for practical optimization and eventual implementation at slow neutron source facilities.

  10. Generalized type II hybrid ARQ scheme using punctured convolutional coding

    NASA Astrophysics Data System (ADS)

    Kallel, Samir; Haccoun, David

    1990-11-01

    A method is presented to construct rate-compatible convolutional (RCC) codes from known high-rate punctured convolutional codes, obtained from best-rate 1/2 codes. The construction method is rather simple and straightforward, and still yields good codes. Moreover, low-rate codes can be obtained without any limit on the lowest achievable code rate. Based on the RCC codes, a generalized type-II hybrid ARQ scheme, which combines the benefits of the modified type-II hybrid ARQ strategy of Hagenauer (1988) with the code-combining ARQ strategy of Chase (1985), is proposed and analyzed. With the proposed generalized type-II hybrid ARQ strategy, the throughput increases as the starting coding rate increases, and as the channel degrades, it tends to merge with the throughput of rate 1/2 type-II hybrid ARQ schemes with code combining, thus allowing the system to be flexible and adaptive to channel conditions, even under wide noise variations and severe degradations.

  11. Classifications of Multispectral Colorectal Cancer Tissues Using Convolution Neural Network

    PubMed Central

    Haj-Hassan, Hawraa; Chaddad, Ahmad; Harkouss, Youssef; Desrosiers, Christian; Toews, Matthew; Tanougast, Camel

    2017-01-01

    Background: Colorectal cancer (CRC) is the third most common cancer among men and women. Its diagnosis in early stages, typically done through the analysis of colon biopsy images, can greatly improve the chances of a successful treatment. This paper proposes to use convolution neural networks (CNNs) to predict three tissue types related to the progression of CRC: benign hyperplasia (BH), intraepithelial neoplasia (IN), and carcinoma (Ca). Methods: Multispectral biopsy images of thirty CRC patients were retrospectively analyzed. Images of tissue samples were divided into three groups, based on their type (10 BH, 10 IN, and 10 Ca). An active contour model was used to segment image regions containing pathological tissues. Tissue samples were classified using a CNN containing convolution, max-pooling, and fully-connected layers. Available tissue samples were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. Results: An accuracy of 99.17% was obtained from segmented image regions, outperforming existing approaches based on traditional feature extraction, and classification techniques. Conclusions: Experimental results demonstrate the effectiveness of CNN for the classification of CRC tissue types, in particular when using presegmented regions of interest. PMID:28400990

  12. Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval.

    PubMed

    Wei, Xiu-Shen; Luo, Jian-Hao; Wu, Jianxin; Zhou, Zhi-Hua

    2017-03-27

    Deep convolutional neural network models pretrained for the ImageNet classification task have been successfully adopted to tasks in other domains, such as texture description and object proposal generation, but these tasks require annotations for images in the new domain. In this paper, we focus on a novel and challenging task in the pure unsupervised setting: fine-grained image retrieval. Even with image labels, fine-grained images are difficult to classify, let alone the unsupervised retrieval task. We propose the Selective Convolutional Descriptor Aggregation (SCDA) method. SCDA firstly localizes the main object in fine-grained images, a step that discards the noisy background and keeps useful deep descriptors. The selected descriptors are then aggregated and dimensionality reduced into a short feature vector using the best practices we found. SCDA is unsupervised, using no image label or bounding box annotation. Experiments on six fine-grained datasets confirm the effectiveness of SCDA for fine-grained image retrieval. Besides, visualization of the SCDA features shows that they correspond to visual attributes (even subtle ones), which might explain SCDA's high mean average precision in fine-grained retrieval. Moreover, on general image retrieval datasets, SCDA achieves comparable retrieval results with state-of-the-art general image retrieval approaches.

  13. Coronary artery calcification (CAC) classification with deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Liu, Xiuming; Wang, Shice; Deng, Yufeng; Chen, Kuan

    2017-03-01

    Coronary artery calcification (CAC) is a typical marker of the coronary artery disease, which is one of the biggest causes of mortality in the U.S. This study evaluates the feasibility of using a deep convolutional neural network (DCNN) to automatically detect CAC in X-ray images. 1768 posteroanterior (PA) view chest X-Ray images from Sichuan Province Peoples Hospital, China were collected retrospectively. Each image is associated with a corresponding diagnostic report written by a trained radiologist (907 normal, 861 diagnosed with CAC). Onequarter of the images were randomly selected as test samples; the rest were used as training samples. DCNN models consisting of 2,4,6 and 8 convolutional layers were designed using blocks of pre-designed CNN layers. Each block was implemented in Theano with Graphics Processing Units (GPU). Human-in-the-loop learning was also performed on a subset of 165 images with framed arteries by trained physicians. The results from the DCNN models were compared to the diagnostic reports. The average diagnostic accuracies for models with 2,4,6,8 layers were 0.85, 0.87, 0.88, and 0.89 respectively. The areas under the curve (AUC) were 0.92, 0.95, 0.95, and 0.96. As the model grows deeper, the AUC or diagnostic accuracies did not have statistically significant changes. The results of this study indicate that DCNN models have promising potential in the field of intelligent medical image diagnosis practice.

  14. Fluence-convolution broad-beam (FCBB) dose calculation.

    PubMed

    Lu, Weiguo; Chen, Mingli

    2010-12-07

    IMRT optimization requires a fast yet relatively accurate algorithm to calculate the iteration dose with small memory demand. In this paper, we present a dose calculation algorithm that approaches these goals. By decomposing the infinitesimal pencil beam (IPB) kernel into the central axis (CAX) component and lateral spread function (LSF) and taking the beam's eye view (BEV), we established a non-voxel and non-beamlet-based dose calculation formula. Both LSF and CAX are determined by a commissioning procedure using the collapsed-cone convolution/superposition (CCCS) method as the standard dose engine. The proposed dose calculation involves a 2D convolution of a fluence map with LSF followed by ray tracing based on the CAX lookup table with radiological distance and divergence correction, resulting in complexity of O(N(3)) both spatially and temporally. This simple algorithm is orders of magnitude faster than the CCCS method. Without pre-calculation of beamlets, its implementation is also orders of magnitude smaller than the conventional voxel-based beamlet-superposition (VBS) approach. We compared the presented algorithm with the CCCS method using simulated and clinical cases. The agreement was generally within 3% for a homogeneous phantom and 5% for heterogeneous and clinical cases. Combined with the 'adaptive full dose correction', the algorithm is well suitable for calculating the iteration dose during IMRT optimization.

  15. Transforming Musical Signals through a Genre Classifying Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Geng, S.; Ren, G.; Ogihara, M.

    2017-05-01

    Convolutional neural networks (CNNs) have been successfully applied on both discriminative and generative modeling for music-related tasks. For a particular task, the trained CNN contains information representing the decision making or the abstracting process. One can hope to manipulate existing music based on this 'informed' network and create music with new features corresponding to the knowledge obtained by the network. In this paper, we propose a method to utilize the stored information from a CNN trained on musical genre classification task. The network was composed of three convolutional layers, and was trained to classify five-second song clips into five different genres. After training, randomly selected clips were modified by maximizing the sum of outputs from the network layers. In addition to the potential of such CNNs to produce interesting audio transformation, more information about the network and the original music could be obtained from the analysis of the generated features since these features indicate how the network 'understands' the music.

  16. Multichannel Convolutional Neural Network for Biological Relation Extraction

    PubMed Central

    Quan, Chanqin; Sun, Xiao; Bai, Wenjun

    2016-01-01

    The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are susceptible to the issues of “vocabulary gap” and data sparseness and the unattainable automation process in feature extraction. To address aforementioned issues, in this work, we propose a multichannel convolutional neural network (MCCNN) for automated biomedical relation extraction. The proposed model has the following two contributions: (1) it enables the fusion of multiple (e.g., five) versions in word embeddings; (2) the need for manual feature engineering can be obviated by automated feature learning with convolutional neural network (CNN). We evaluated our model on two biomedical relation extraction tasks: drug-drug interaction (DDI) extraction and protein-protein interaction (PPI) extraction. For DDI task, our system achieved an overall f-score of 70.2% compared to the standard linear SVM based system (e.g., 67.0%) on DDIExtraction 2013 challenge dataset. And for PPI task, we evaluated our system on Aimed and BioInfer PPI corpus; our system exceeded the state-of-art ensemble SVM system by 2.7% and 5.6% on f-scores. PMID:28053977

  17. A Mathematical Motivation for Complex-Valued Convolutional Networks.

    PubMed

    Tygert, Mark; Bruna, Joan; Chintala, Soumith; LeCun, Yann; Piantino, Serkan; Szlam, Arthur

    2016-05-01

    A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with complex-valued vectors, followed by (2) taking the absolute value of every entry of the resulting vectors, followed by (3) local averaging. For processing real-valued random vectors, complex-valued convnets can be viewed as data-driven multiscale windowed power spectra, data-driven multiscale windowed absolute spectra, data-driven multiwavelet absolute values, or (in their most general configuration) data-driven nonlinear multiwavelet packets. Indeed, complex-valued convnets can calculate multiscale windowed spectra when the convnet filters are windowed complex-valued exponentials. Standard real-valued convnets, using rectified linear units (ReLUs), sigmoidal (e.g., logistic or tanh) nonlinearities, or max pooling, for example, do not obviously exhibit the same exact correspondence with data-driven wavelets (whereas for complex-valued convnets, the correspondence is much more than just a vague analogy). Courtesy of the exact correspondence, the remarkably rich and rigorous body of mathematical analysis for wavelets applies directly to (complex-valued) convnets.

  18. Classification of Histology Sections via Multispectral Convolutional Sparse Coding.

    PubMed

    Zhou, Yin; Chang, Hang; Barner, Kenneth; Spellman, Paul; Parvin, Bahram

    2014-06-01

    Image-based classification of histology sections plays an important role in predicting clinical outcomes. However this task is very challenging due to the presence of large technical variations (e.g., fixation, staining) and biological heterogeneities (e.g., cell type, cell state). In the field of biomedical imaging, for the purposes of visualization and/or quantification, different stains are typically used for different targets of interest (e.g., cellular/subcellular events), which generates multi-spectrum data (images) through various types of microscopes and, as a result, provides the possibility of learning biological-component-specific features by exploiting multispectral information. We propose a multispectral feature learning model that automatically learns a set of convolution filter banks from separate spectra to efficiently discover the intrinsic tissue morphometric signatures, based on convolutional sparse coding (CSC). The learned feature representations are then aggregated through the spatial pyramid matching framework (SPM) and finally classified using a linear SVM. The proposed system has been evaluated using two large-scale tumor cohorts, collected from The Cancer Genome Atlas (TCGA). Experimental results show that the proposed model 1) outperforms systems utilizing sparse coding for unsupervised feature learning (e.g., PSD-SPM [5]); 2) is competitive with systems built upon features with biological prior knowledge (e.g., SMLSPM [4]).

  19. Deep Convolutional Neural Networks for large-scale speech tasks.

    PubMed

    Sainath, Tara N; Kingsbury, Brian; Saon, George; Soltau, Hagen; Mohamed, Abdel-rahman; Dahl, George; Ramabhadran, Bhuvana

    2015-04-01

    Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and model spectral correlations which exist in signals. Since speech signals exhibit both of these properties, we hypothesize that CNNs are a more effective model for speech compared to Deep Neural Networks (DNNs). In this paper, we explore applying CNNs to large vocabulary continuous speech recognition (LVCSR) tasks. First, we determine the appropriate architecture to make CNNs effective compared to DNNs for LVCSR tasks. Specifically, we focus on how many convolutional layers are needed, what is an appropriate number of hidden units, what is the best pooling strategy. Second, investigate how to incorporate speaker-adapted features, which cannot directly be modeled by CNNs as they do not obey locality in frequency, into the CNN framework. Third, given the importance of sequence training for speech tasks, we introduce a strategy to use ReLU+dropout during Hessian-free sequence training of CNNs. Experiments on 3 LVCSR tasks indicate that a CNN with the proposed speaker-adapted and ReLU+dropout ideas allow for a 12%-14% relative improvement in WER over a strong DNN system, achieving state-of-the art results in these 3 tasks. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Convolutional Neural Network Based Fault Detection for Rotating Machinery

    NASA Astrophysics Data System (ADS)

    Janssens, Olivier; Slavkovikj, Viktor; Vervisch, Bram; Stockman, Kurt; Loccufier, Mia; Verstockt, Steven; Van de Walle, Rik; Van Hoecke, Sofie

    2016-09-01

    Vibration analysis is a well-established technique for condition monitoring of rotating machines as the vibration patterns differ depending on the fault or machine condition. Currently, mainly manually-engineered features, such as the ball pass frequencies of the raceway, RMS, kurtosis an crest, are used for automatic fault detection. Unfortunately, engineering and interpreting such features requires a significant level of human expertise. To enable non-experts in vibration analysis to perform condition monitoring, the overhead of feature engineering for specific faults needs to be reduced as much as possible. Therefore, in this article we propose a feature learning model for condition monitoring based on convolutional neural networks. The goal of this approach is to autonomously learn useful features for bearing fault detection from the data itself. Several types of bearing faults such as outer-raceway faults and lubrication degradation are considered, but also healthy bearings and rotor imbalance are included. For each condition, several bearings are tested to ensure generalization of the fault-detection system. Furthermore, the feature-learning based approach is compared to a feature-engineering based approach using the same data to objectively quantify their performance. The results indicate that the feature-learning system, based on convolutional neural networks, significantly outperforms the classical feature-engineering based approach which uses manually engineered features and a random forest classifier. The former achieves an accuracy of 93.61 percent and the latter an accuracy of 87.25 percent.

  1. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

    PubMed

    Dürr, Oliver; Sick, Beate

    2016-10-01

    Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening-based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%. © 2016 Society for Laboratory Automation and Screening.

  2. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

    PubMed Central

    Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

    2017-01-01

    Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction. PMID:28672867

  3. Video-based face recognition via convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Bao, Tianlong; Ding, Chunhui; Karmoshi, Saleem; Zhu, Ming

    2017-06-01

    Face recognition has been widely studied recently while video-based face recognition still remains a challenging task because of the low quality and large intra-class variation of video captured face images. In this paper, we focus on two scenarios of video-based face recognition: 1)Still-to-Video(S2V) face recognition, i.e., querying a still face image against a gallery of video sequences; 2)Video-to-Still(V2S) face recognition, in contrast to S2V scenario. A novel method was proposed in this paper to transfer still and video face images to an Euclidean space by a carefully designed convolutional neural network, then Euclidean metrics are used to measure the distance between still and video images. Identities of still and video images that group as pairs are used as supervision. In the training stage, a joint loss function that measures the Euclidean distance between the predicted features of training pairs and expanding vectors of still images is optimized to minimize the intra-class variation while the inter-class variation is guaranteed due to the large margin of still images. Transferred features are finally learned via the designed convolutional neural network. Experiments are performed on COX face dataset. Experimental results show that our method achieves reliable performance compared with other state-of-the-art methods.

  4. Convolutional neural network architectures for predicting DNA–protein binding

    PubMed Central

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  5. Classifications of Multispectral Colorectal Cancer Tissues Using Convolution Neural Network.

    PubMed

    Haj-Hassan, Hawraa; Chaddad, Ahmad; Harkouss, Youssef; Desrosiers, Christian; Toews, Matthew; Tanougast, Camel

    2017-01-01

    Colorectal cancer (CRC) is the third most common cancer among men and women. Its diagnosis in early stages, typically done through the analysis of colon biopsy images, can greatly improve the chances of a successful treatment. This paper proposes to use convolution neural networks (CNNs) to predict three tissue types related to the progression of CRC: benign hyperplasia (BH), intraepithelial neoplasia (IN), and carcinoma (Ca). Multispectral biopsy images of thirty CRC patients were retrospectively analyzed. Images of tissue samples were divided into three groups, based on their type (10 BH, 10 IN, and 10 Ca). An active contour model was used to segment image regions containing pathological tissues. Tissue samples were classified using a CNN containing convolution, max-pooling, and fully-connected layers. Available tissue samples were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. An accuracy of 99.17% was obtained from segmented image regions, outperforming existing approaches based on traditional feature extraction, and classification techniques. Experimental results demonstrate the effectiveness of CNN for the classification of CRC tissue types, in particular when using presegmented regions of interest.

  6. Convolutional neural network features based change detection in satellite images

    NASA Astrophysics Data System (ADS)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  7. Using convolutional decoding to improve time delay and phase estimation in digital communications

    DOEpatents

    Ormesher, Richard C.; Mason, John J.

    2010-01-26

    The time delay and/or phase of a communication signal received by a digital communication receiver can be estimated based on a convolutional decoding operation that the communication receiver performs on the received communication signal. If the original transmitted communication signal has been spread according to a spreading operation, a corresponding despreading operation can be integrated into the convolutional decoding operation.

  8. Experimental study of current loss and plasma formation in the Z machine post-hole convolute

    NASA Astrophysics Data System (ADS)

    Gomez, M. R.; Gilgenbach, R. M.; Cuneo, M. E.; Jennings, C. A.; McBride, R. D.; Waisman, E. M.; Hutsel, B. T.; Stygar, W. A.; Rose, D. V.; Maron, Y.

    2017-01-01

    The Z pulsed-power generator at Sandia National Laboratories drives high energy density physics experiments with load currents of up to 26 MA. Z utilizes a double post-hole convolute to combine the current from four parallel magnetically insulated transmission lines into a single transmission line just upstream of the load. Current loss is observed in most experiments and is traditionally attributed to inefficient convolute performance. The apparent loss current varies substantially for z-pinch loads with different inductance histories; however, a similar convolute impedance history is observed for all load types. This paper details direct spectroscopic measurements of plasma density, temperature, and apparent and actual plasma closure velocities within the convolute. Spectral measurements indicate a correlation between impedance collapse and plasma formation in the convolute. Absorption features in the spectra show the convolute plasma consists primarily of hydrogen, which likely forms from desorbed electrode contaminant species such as H2O , H2 , and hydrocarbons. Plasma densities increase from 1 ×1016 cm-3 (level of detectability) just before peak current to over 1 ×1017 cm-3 at stagnation (tens of ns later). The density seems to be highest near the cathode surface, with an apparent cathode to anode plasma velocity in the range of 35 - 50 cm /μ s . Similar plasma conditions and convolute impedance histories are observed in experiments with high and low losses, suggesting that losses are driven largely by load dynamics, which determine the voltage on the convolute.

  9. There is no MacWilliams identity for convolutional codes. [transmission gain comparison

    NASA Technical Reports Server (NTRS)

    Shearer, J. B.; Mceliece, R. J.

    1977-01-01

    An example is provided of two convolutional codes that have the same transmission gain but whose dual codes do not. This shows that no analog of the MacWilliams identity for block codes can exist relating the transmission gains of a convolutional code and its dual.

  10. Convolution algorithm for normalization constant evaluation in queuing system with random requirements

    NASA Astrophysics Data System (ADS)

    Samouylov, K.; Sopin, E.; Vikhrova, O.; Shorgin, S.

    2017-07-01

    We suggest a convolution algorithm for calculating the normalization constant for stationary probabilities of a multiserver queuing system with random resource requirements. Our algorithm significantly reduces computing time of the stationary probabilities and system characteristics such as blocking probabilities and average number of occupied resources. The algorithm aims to avoid calculation of k-fold convolutions and reasonably use memory resources.

  11. Linear diffusion-wave channel routing using a discrete Hayami convolution method

    Treesearch

    Li Wang; Joan Q. Wu; William J. Elliot; Fritz R. Feidler; Sergey. Lapin

    2014-01-01

    The convolution of an input with a response function has been widely used in hydrology as a means to solve various problems analytically. Due to the high computation demand in solving the functions using numerical integration, it is often advantageous to use the discrete convolution instead of the integration of the continuous functions. This approach greatly reduces...

  12. Manufacturing Technology for Nonautoclave Fabrication of Composite Structures

    DTIC Science & Technology

    1985-06-01

    fabricating bags using calendered rubber or solid rubber tooling. To improve the bag and reduce its cost, silicone rubber was sprayed on the tool to shape a...to fabricate the cocure bag. The silicone rubber bag for cover laminate staging and curing was fabricated using calendered rubber sheet. The bag was... Fabrication Matrix . . . . . . . . . . . . . . 42 XV Soundnes Validation Test Results . . . . . . . . ............... .. 44 XVI Sprayable Silicone

  13. Modeling of woven fabric structures based on fourier image analysis.

    PubMed

    Escofet, J; Millán, M S; Ralló, M

    2001-12-01

    The periodic woven structures of fabrics can be defined on the basis of the convolution theorem. Here an elementary unit with the minimum number of thread crossings and a nonrectangular two-dimensional comb function for the pattern of repetition is used to define woven structures. The expression derived is more compact than the conventional diagram for weaving, and the parameters that one needs to determine a given fabric can easily be extracted from its Fourier transform. Several results with real samples of the most common structures-plain, twill, and satin-are presented.

  14. The effect of whitening transformation on pooling operations in convolutional autoencoders

    NASA Astrophysics Data System (ADS)

    Li, Zuhe; Fan, Yangyu; Liu, Weihua

    2015-12-01

    Convolutional autoencoders (CAEs) are unsupervised feature extractors for high-resolution images. In the pre-processing step, whitening transformation has widely been adopted to remove redundancy by making adjacent pixels less correlated. Pooling is a biologically inspired operation to reduce the resolution of feature maps and achieve spatial invariance in convolutional neural networks. Conventionally, pooling methods are mainly determined empirically in most previous work. Therefore, our main purpose is to study the relationship between whitening processing and pooling operations in convolutional autoencoders for image classification. We propose an adaptive pooling approach based on the concepts of information entropy to test the effect of whitening on pooling in different conditions. Experimental results on benchmark datasets indicate that the performance of pooling strategies is associated with the distribution of feature activations, which can be affected by whitening processing. This provides guidance for the selection of pooling methods in convolutional autoencoders and other convolutional neural networks.

  15. Experimental Measurements of the Convolute Plasma on the Z-Machine*

    NASA Astrophysics Data System (ADS)

    Gomez, M. R.; Gilgenbach, R. M.; Cuneo, M. E.; McBride, R. D.; Rochau, G. A.; Jones, B.; Ampleford, D. J.; Sinars, D. B.; Bailey, J. E.; Stygar, W. A.; Savage, M. E.; Jones, M.; Edens, A. D.; Lopez, M. R.; Stambulchik, E.; Maron, Y.; Rose, D. V.; Welch, D. R.

    2011-10-01

    Post-hole convolutes are used in large pulsed power devices to combine the current from several self-magnetically insulated transmission lines at the load. The efficiency of Z's post-hole convolute has decreased with increasing electrical power. Losses as high as 20% of the peak current have been recorded on the most lossy shots. Spectroscopic measurements of the plasma that forms in the convolute are underway. Initial results show that there is a strong correlation between convolute plasma density and the load. This presentation will cover convolute plasma behavior and loss current for several load configurations on the Z-Machine. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  16. Photovoltaic fabrics

    DTIC Science & Technology

    2015-04-22

    during wire fabrication. Weaving was demonstrated for both military-type nylon -cotton blend (NYCO) warp fibers and cotton-polyester warp fibers. A...Lowell, MA 01852 14. ABSTRACT This report describes a project to improve photovoltaic fabrics. It had four objectives: 1) Efficiency – make PV wires on...a continuous basis that exhibit 7% efficiency; 2) Automated Welding – demonstrate an automated means of interconnecting the electrodes of one wire

  17. Visualization of vasculature with convolution surfaces: method, validation and evaluation.

    PubMed

    Oeltze, Steffen; Preim, Bernhard

    2005-04-01

    We present a method for visualizing vasculature based on clinical computed tomography or magnetic resonance data. The vessel skeleton as well as the diameter information per voxel serve as input. Our method adheres to these data, while producing smooth transitions at branchings and closed, rounded ends by means of convolution surfaces. We examine the filter design with respect to irritating bulges, unwanted blending and the correct visualization of the vessel diameter. The method has been applied to a large variety of anatomic trees. We discuss the validation of the method by means of a comparison to other visualization methods. Surface distance measures are carried out to perform a quantitative validation. Furthermore, we present the evaluation of the method which has been accomplished on the basis of a survey by 11 radiologists and surgeons.

  18. Training strategy for convolutional neural networks in pedestrian gender classification

    NASA Astrophysics Data System (ADS)

    Ng, Choon-Boon; Tay, Yong-Haur; Goi, Bok-Min

    2017-06-01

    In this work, we studied a strategy for training a convolutional neural network in pedestrian gender classification with limited amount of labeled training data. Unsupervised learning by k-means clustering on pedestrian images was used to learn the filters to initialize the first layer of the network. As a form of pre-training, supervised learning for the related task of pedestrian classification was performed. Finally, the network was fine-tuned for gender classification. We found that this strategy improved the network's generalization ability in gender classification, achieving better test results when compared to random weights initialization and slightly more beneficial than merely initializing the first layer filters by unsupervised learning. This shows that unsupervised learning followed by pre-training with pedestrian images is an effective strategy to learn useful features for pedestrian gender classification.

  19. Fast convolution with free-space Green's functions

    NASA Astrophysics Data System (ADS)

    Vico, Felipe; Greengard, Leslie; Ferrando, Miguel

    2016-10-01

    We introduce a fast algorithm for computing volume potentials - that is, the convolution of a translation invariant, free-space Green's function with a compactly supported source distribution defined on a uniform grid. The algorithm relies on regularizing the Fourier transform of the Green's function by cutting off the interaction in physical space beyond the domain of interest. This permits the straightforward application of trapezoidal quadrature and the standard FFT, with superalgebraic convergence for smooth data. Moreover, the method can be interpreted as employing a Nystrom discretization of the corresponding integral operator, with matrix entries which can be obtained explicitly and rapidly. This is of use in the design of preconditioners or fast direct solvers for a variety of volume integral equations. The method proposed permits the computation of any derivative of the potential, at the cost of an additional FFT.

  20. Truncation Depth Rule-of-Thumb for Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Moision, Bruce

    2009-01-01

    In this innovation, it is shown that a commonly used rule of thumb (that the truncation depth of a convolutional code should be five times the memory length, m, of the code) is accurate only for rate 1/2 codes. In fact, the truncation depth should be 2.5 m/(1 - r), where r is the code rate. The accuracy of this new rule is demonstrated by tabulating the distance properties of a large set of known codes. This new rule was derived by bounding the losses due to truncation as a function of the code rate. With regard to particular codes, a good indicator of the required truncation depth is the path length at which all paths that diverge from a particular path have accumulated the minimum distance of the code. It is shown that the new rule of thumb provides an accurate prediction of this depth for codes of varying rates.

  1. Radio frequency interference mitigation using deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Akeret, J.; Chang, C.; Lucchi, A.; Refregier, A.

    2017-01-01

    We propose a novel approach for mitigating radio frequency interference (RFI) signals in radio data using the latest advances in deep learning. We employ a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. We train and assess the performance of this network using the HIDE &SEEK radio data simulation and processing packages, as well as early Science Verification data acquired with the 7m single-dish telescope at the Bleien Observatory. We find that our U-Net implementation is showing competitive accuracy to classical RFI mitigation algorithms such as SEEK's SUMTHRESHOLD implementation. We publish our U-Net software package on GitHub under GPLv3 license.

  2. Deep convolutional neural network for prostate MR segmentation

    NASA Astrophysics Data System (ADS)

    Tian, Zhiqiang; Liu, Lizhi; Fei, Baowei

    2017-03-01

    Automatic segmentation of the prostate in magnetic resonance imaging (MRI) has many applications in prostate cancer diagnosis and therapy. We propose a deep fully convolutional neural network (CNN) to segment the prostate automatically. Our deep CNN model is trained end-to-end in a single learning stage based on prostate MR images and the corresponding ground truths, and learns to make inference for pixel-wise segmentation. Experiments were performed on our in-house data set, which contains prostate MR images of 20 patients. The proposed CNN model obtained a mean Dice similarity coefficient of 85.3%+/-3.2% as compared to the manual segmentation. Experimental results show that our deep CNN model could yield satisfactory segmentation of the prostate.

  3. $\\mathtt {Deepr}$: A Convolutional Net for Medical Records.

    PubMed

    Nguyen, Phuoc; Tran, Truyen; Wickramasinghe, Nilmini; Venkatesh, Svetha

    2017-01-01

    Feature engineering remains a major bottleneck when creating predictive systems from electronic medical records. At present, an important missing element is detecting predictive regular clinical motifs from irregular episodic records. We present Deepr (short for Deep record), a new end-to-end deep learning system that learns to extract features from medical records and predicts future risk automatically. Deepr transforms a record into a sequence of discrete elements separated by coded time gaps and hospital transfers. On top of the sequence is a convolutional neural net that detects and combines predictive local clinical motifs to stratify the risk. Deepr permits transparent inspection and visualization of its inner working. We validate Deepr on hospital data to predict unplanned readmission after discharge. Deepr achieves superior accuracy compared to traditional techniques, detects meaningful clinical motifs, and uncovers the underlying structure of the disease and intervention space.

  4. Learning to Generate Chairs, Tables and Cars with Convolutional Networks.

    PubMed

    Dosovitskiy, Alexey; Springenberg, Jost Tobias; Tatarchenko, Maxim; Brox, Thomas

    2017-04-01

    We train generative 'up-convolutional' neural networks which are able to generate images of objects given object style, viewpoint, and color. We train the networks on rendered 3D models of chairs, tables, and cars. Our experiments show that the networks do not merely learn all images by heart, but rather find a meaningful representation of 3D models allowing them to assess the similarity of different models, interpolate between given views to generate the missing ones, extrapolate views, and invent new objects not present in the training set by recombining training instances, or even two different object classes. Moreover, we show that such generative networks can be used to find correspondences between different objects from the dataset, outperforming existing approaches on this task.

  5. Rapid Exact Signal Scanning With Deep Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Thom, Markus; Gritschneder, Franz

    2017-03-01

    A rigorous formulation of the dynamics of a signal processing scheme aimed at dense signal scanning without any loss in accuracy is introduced and analyzed. Related methods proposed in the recent past lack a satisfactory analysis of whether they actually fulfill any exactness constraints. This is improved through an exact characterization of the requirements for a sound sliding window approach. The tools developed in this paper are especially beneficial if Convolutional Neural Networks are employed, but can also be used as a more general framework to validate related approaches to signal scanning. The proposed theory helps to eliminate redundant computations and renders special case treatment unnecessary, resulting in a dramatic boost in efficiency particularly on massively parallel processors. This is demonstrated both theoretically in a computational complexity analysis and empirically on modern parallel processors.

  6. Protein-Ligand Scoring with Convolutional Neural Networks.

    PubMed

    Ragoza, Matthew; Hochuli, Joshua; Idrobo, Elisa; Sunseri, Jocelyn; Koes, David Ryan

    2017-04-11

    Computational approaches to drug discovery can reduce the time and cost associated with experimental assays and enable the screening of novel chemotypes. Structure-based drug design methods rely on scoring functions to rank and predict binding affinities and poses. The ever-expanding amount of protein-ligand binding and structural data enables the use of deep machine learning techniques for protein-ligand scoring. We describe convolutional neural network (CNN) scoring functions that take as input a comprehensive three-dimensional (3D) representation of a protein-ligand interaction. A CNN scoring function automatically learns the key features of protein-ligand interactions that correlate with binding. We train and optimize our CNN scoring functions to discriminate between correct and incorrect binding poses and known binders and nonbinders. We find that our CNN scoring function outperforms the AutoDock Vina scoring function when ranking poses both for pose prediction and virtual screening.

  7. Stability Training for Convolutional Neural Nets in LArTPC

    NASA Astrophysics Data System (ADS)

    Lindsay, Matt; Wongjirad, Taritree

    2017-01-01

    Convolutional Neural Nets (CNNs) are the state of the art for many problems in computer vision and are a promising method for classifying interactions in Liquid Argon Time Projection Chambers (LArTPCs) used in neutrino oscillation experiments. Despite the good performance of CNN's, they are not without drawbacks, chief among them is vulnerability to noise and small perturbations to the input. One solution to this problem is a modification to the learning process called Stability Training developed by Zheng et al. We verify existing work and demonstrate volatility caused by simple Gaussian noise and also that the volatility can be nearly eliminated with Stability Training. We then go further and show that a traditional CNN is also vulnerable to realistic experimental noise and that a stability trained CNN remains accurate despite noise. This further adds to the optimism for CNNs for work in LArTPCs and other applications.

  8. Modifying real convolutional codes for protecting digital filtering systems

    NASA Technical Reports Server (NTRS)

    Redinbo, G. R.; Zagar, Bernhard

    1993-01-01

    A novel method is proposed for protecting digital filters from temporary and permanent failures that are not easily detected by conventional fault-tolerant computer design principles, on the basis of the error-detecting properties of real convolutional codes. Erroneous behavior is detected by externally comparing the calculated and regenerated parity samples. Great simplifications are obtainable by modifying the code structure to yield simplified parity channels with finite impulse response structures. A matrix equation involving the original parity values of the code and the polynomial of the digital filter's transfer function is formed, and row manipulations separate this equation into a set of homogeneous equations constraining the modifying scaling coefficients and another set which defines the code parity values' implementation.

  9. A convolution model of rock bed thermal storage units

    NASA Astrophysics Data System (ADS)

    Sowell, E. F.; Curry, R. L.

    1980-01-01

    A method is presented whereby a packed-bed thermal storage unit is dynamically modeled for bi-directional flow and arbitrary input flow stream temperature variations. The method is based on the principle of calculating the output temperature as the sum of earlier input temperatures, each multiplied by a predetermined 'response factor', i.e., discrete convolution. A computer implementation of the scheme, in the form of a subroutine for a widely used solar simulation program (TRNSYS) is described and numerical results compared with other models. Also, a method for efficient computation of the required response factors is described; this solution is for a triangular input pulse, previously unreported, although the solution method is also applicable for other input functions. This solution requires a single integration of a known function which is easily carried out numerically to the required precision.

  10. Learning Building Extraction in Aerial Scenes with Convolutional Networks.

    PubMed

    Yuan, Jiangye

    2017-09-11

    Extracting buildings from aerial scene images is an important task with many applications. However, this task is highly difficult to automate due to extremely large variations of building appearances, and still heavily relies on manual work. To attack this problem, we design a deep convolutional network with a simple structure that integrates activation from multiple layers for pixel-wise prediction, and introduce the signed distance function of building boundaries as the output representation, which has an enhanced representation power. To train the network, we leverage abundant building footprint data from geographic information systems (GIS) to generate large amounts of labeled data. The trained model achieves a superior performance on datasets that are significantly larger and more complex than those used in prior work, demonstrating that the proposed method provides a promising and scalable solution for automating this labor-intensive task.

  11. Invariant Descriptor Learning Using a Siamese Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Chen, L.; Rottensteiner, F.; Heipke, C.

    2016-06-01

    In this paper we describe learning of a descriptor based on the Siamese Convolutional Neural Network (CNN) architecture and evaluate our results on a standard patch comparison dataset. The descriptor learning architecture is composed of an input module, a Siamese CNN descriptor module and a cost computation module that is based on the L2 Norm. The cost function we use pulls the descriptors of matching patches close to each other in feature space while pushing the descriptors for non-matching pairs away from each other. Compared to related work, we optimize the training parameters by combining a moving average strategy for gradients and Nesterov's Accelerated Gradient. Experiments show that our learned descriptor reaches a good performance and achieves state-of-art results in terms of the false positive rate at a 95 % recall rate on standard benchmark datasets.

  12. Finding the complete path and weight enumerators of convolutional codes

    NASA Technical Reports Server (NTRS)

    Onyszchuk, I.

    1990-01-01

    A method for obtaining the complete path enumerator T(D, L, I) of a convolutional code is described. A system of algebraic equations is solved, using a new algorithm for computing determinants, to obtain T(D, L, I) for the (7,1/2) NASA standard code. Generating functions, derived from T(D, L, I) are used to upper bound Viterbi decoder error rates. This technique is currently feasible for constraint length K less than 10 codes. A practical, fast algorithm is presented for computing the leading nonzero coefficients of the generating functions used to bound the performance of constraint length K less than 20 codes. Code profiles with about 50 nonzero coefficients are obtained with this algorithm for the experimental K = 15, rate 1/4, code in the Galileo mission and for the proposed K = 15, rate 1/6, 2-dB code.

  13. Tomography by iterative convolution - Empirical study and application to interferometry

    NASA Technical Reports Server (NTRS)

    Vest, C. M.; Prikryl, I.

    1984-01-01

    An algorithm for computer tomography has been developed that is applicable to reconstruction from data having incomplete projections because an opaque object blocks some of the probing radiation as it passes through the object field. The algorithm is based on iteration between the object domain and the projection (Radon transform) domain. Reconstructions are computed during each iteration by the well-known convolution method. Although it is demonstrated that this algorithm does not converge, an empirically justified criterion for terminating the iteration when the most accurate estimate has been computed is presented. The algorithm has been studied by using it to reconstruct several different object fields with several different opaque regions. It also has been used to reconstruct aerodynamic density fields from interferometric data recorded in wind tunnel tests.

  14. Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review.

    PubMed

    Rawat, Waseem; Wang, Zenghui

    2017-09-01

    Convolutional neural networks (CNNs) have been applied to visual tasks since the late 1980s. However, despite a few scattered applications, they were dormant until the mid-2000s when developments in computing power and the advent of large amounts of labeled data, supplemented by improved algorithms, contributed to their advancement and brought them to the forefront of a neural network renaissance that has seen rapid progression since 2012. In this review, which focuses on the application of CNNs to image classification tasks, we cover their development, from their predecessors up to recent state-of-the-art deep learning systems. Along the way, we analyze (1) their early successes, (2) their role in the deep learning renaissance, (3) selected symbolic works that have contributed to their recent popularity, and (4) several improvement attempts by reviewing contributions and challenges of over 300 publications. We also introduce some of their current trends and remaining challenges.

  15. Towards Better Analysis of Deep Convolutional Neural Networks.

    PubMed

    Liu, Mengchen; Shi, Jiaxin; Li, Zhen; Li, Chongxuan; Zhu, Jun; Liu, Shixia

    2017-01-01

    Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification. However, the development of high-quality deep models typically relies on a substantial amount of trial-and-error, as there is still no clear understanding of when and why a deep model works. In this paper, we present a visual analytics approach for better understanding, diagnosing, and refining deep CNNs. We formulate a deep CNN as a directed acyclic graph. Based on this formulation, a hybrid visualization is developed to disclose the multiple facets of each neuron and the interactions between them. In particular, we introduce a hierarchical rectangle packing algorithm and a matrix reordering algorithm to show the derived features of a neuron cluster. We also propose a biclustering-based edge bundling method to reduce visual clutter caused by a large number of connections between neurons. We evaluated our method on a set of CNNs and the results are generally favorable.

  16. Convolution quadrature for the wave equation with impedance boundary conditions

    NASA Astrophysics Data System (ADS)

    Sauter, S. A.; Schanz, M.

    2017-04-01

    We consider the numerical solution of the wave equation with impedance boundary conditions and start from a boundary integral formulation for its discretization. We develop the generalized convolution quadrature (gCQ) to solve the arising acoustic retarded potential integral equation for this impedance problem. For the special case of scattering from a spherical object, we derive representations of analytic solutions which allow to investigate the effect of the impedance coefficient on the acoustic pressure analytically. We have performed systematic numerical experiments to study the convergence rates as well as the sensitivity of the acoustic pressure from the impedance coefficients. Finally, we apply this method to simulate the acoustic pressure in a building with a fairly complicated geometry and to study the influence of the impedance coefficient also in this situation.

  17. Structured learning via convolutional neural networks for vehicle detection

    NASA Astrophysics Data System (ADS)

    Maqueda, Ana I.; del Blanco, Carlos R.; Jaureguizar, Fernando; García, Narciso

    2017-05-01

    One of the main tasks in a vision-based traffic monitoring system is the detection of vehicles. Recently, deep neural networks have been successfully applied to this end, outperforming previous approaches. However, most of these works generally rely on complex and high-computational region proposal networks. Others employ deep neural networks as a segmentation strategy to achieve a semantic representation of the object of interest, which has to be up-sampled later. In this paper, a new design for a convolutional neural network is applied to vehicle detection in highways for traffic monitoring. This network generates a spatially structured output that encodes the vehicle locations. Promising results have been obtained in the GRAM-RTM dataset.

  18. Deep convolutional neural networks for ATR from SAR imagery

    NASA Astrophysics Data System (ADS)

    Morgan, David A. E.

    2015-05-01

    Deep architectures for classification and representation learning have recently attracted significant attention within academia and industry, with many impressive results across a diverse collection of problem sets. In this work we consider the specific application of Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR) data from the MSTAR public release data set. The classification performance achieved using a Deep Convolutional Neural Network (CNN) on this data set was found to be competitive with existing methods considered to be state-of-the-art. Unlike most existing algorithms, this approach can learn discriminative feature sets directly from training data instead of requiring pre-specification or pre-selection by a human designer. We show how this property can be exploited to efficiently adapt an existing classifier to recognise a previously unseen target and discuss potential practical applications.

  19. Discovering characteristic landmarks on ancient coins using convolutional networks

    NASA Astrophysics Data System (ADS)

    Kim, Jongpil; Pavlovic, Vladimir

    2017-01-01

    We propose a method to find characteristic landmarks and recognize ancient Roman imperial coins using deep convolutional neural networks (CNNs) combined with expert-designed domain hierarchies. We first propose a framework to recognize Roman coins that exploits the hierarchical knowledge structure embedded in the coin domain, which we combine with the CNN-based category classifiers. We next formulate an optimization problem to discover class-specific salient coin regions. Analysis of discovered salient regions confirms that they are largely consistent with human expert annotations. Experimental results show that the proposed framework is able to effectively recognize ancient Roman coins as well as successfully identify landmarks on the coins. For this research, we have collected a Roman coin dataset where all coins are annotated and consist of obverse (head) and reverse (tail) images.

  20. Convolution properties for certain classes of multivalent functions

    NASA Astrophysics Data System (ADS)

    Sokól, Janusz; Trojnar-Spelina, Lucyna

    2008-01-01

    Recently N.E. Cho, O.S. Kwon and H.M. Srivastava [Nak Eun Cho, Oh Sang Kwon, H.M. Srivastava, Inclusion relationships and argument properties for certain subclasses of multivalent functions associated with a family of linear operators, J. Math. Anal. Appl. 292 (2004) 470-483] have introduced the class of multivalent analytic functions and have given a number of results. This class has been defined by means of a special linear operator associated with the Gaussian hypergeometric function. In this paper we have extended some of the previous results and have given other properties of this class. We have made use of differential subordinations and properties of convolution in geometric function theory.

  1. Low-dose CT via convolutional neural network

    PubMed Central

    Chen, Hu; Zhang, Yi; Zhang, Weihua; Liao, Peixi; Li, Ke; Zhou, Jiliu; Wang, Ge

    2017-01-01

    In order to reduce the potential radiation risk, low-dose CT has attracted an increasing attention. However, simply lowering the radiation dose will significantly degrade the image quality. In this paper, we propose a new noise reduction method for low-dose CT via deep learning without accessing original projection data. A deep convolutional neural network is here used to map low-dose CT images towards its corresponding normal-dose counterparts in a patch-by-patch fashion. Qualitative results demonstrate a great potential of the proposed method on artifact reduction and structure preservation. In terms of the quantitative metrics, the proposed method has showed a substantial improvement on PSNR, RMSE and SSIM than the competing state-of-art methods. Furthermore, the speed of our method is one order of magnitude faster than the iterative reconstruction and patch-based image denoising methods. PMID:28270976

  2. A shallow convolutional neural network for blind image sharpness assessment.

    PubMed

    Yu, Shaode; Wu, Shibin; Wang, Lei; Jiang, Fan; Xie, Yaoqin; Li, Leida

    2017-01-01

    Blind image quality assessment can be modeled as feature extraction followed by score prediction. It necessitates considerable expertise and efforts to handcraft features for optimal representation of perceptual image quality. This paper addresses blind image sharpness assessment by using a shallow convolutional neural network (CNN). The network takes single feature layer to unearth intrinsic features for image sharpness representation and utilizes multilayer perceptron (MLP) to rate image quality. Different from traditional methods, CNN integrates feature extraction and score prediction into an optimization procedure and retrieves features automatically from raw images. Moreover, its prediction performance can be enhanced by replacing MLP with general regression neural network (GRNN) and support vector regression (SVR). Experiments on Gaussian blur images from LIVE-II, CSIQ, TID2008 and TID2013 demonstrate that CNN features with SVR achieves the best overall performance, indicating high correlation with human subjective judgment.

  3. Drug-Drug Interaction Extraction via Convolutional Neural Networks.

    PubMed

    Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong

    2016-01-01

    Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a large number of manually defined features. Recently, convolutional neural networks (CNN), a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%.

  4. Convolutional Neural Networks for patient-specific ECG classification.

    PubMed

    Kiranyaz, Serkan; Ince, Turker; Hamila, Ridha; Gabbouj, Moncef

    2015-01-01

    We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and classification into a unified learner. In this way, a dedicated CNN will be trained for each patient by using relatively small common and patient-specific training data and thus it can also be used to classify long ECG records such as Holter registers in a fast and accurate manner. Alternatively, such a solution can conveniently be used for real-time ECG monitoring and early alert system on a light-weight wearable device. The experimental results demonstrate that the proposed system achieves a superior classification performance for the detection of ventricular ectopic beats (VEB) and supraventricular ectopic beats (SVEB).

  5. Small convolution kernels for high-fidelity image restoration

    NASA Technical Reports Server (NTRS)

    Reichenbach, Stephen E.; Park, Stephen K.

    1991-01-01

    An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

  6. An effective convolutional neural network model for Chinese sentiment analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Chen, Mengdong; Liu, Lianzhong; Wang, Yadong

    2017-06-01

    Nowadays microblog is getting more and more popular. People are increasingly accustomed to expressing their opinions on Twitter, Facebook and Sina Weibo. Sentiment analysis of microblog has received significant attention, both in academia and in industry. So far, Chinese microblog exploration still needs lots of further work. In recent years CNN has also been used to deal with NLP tasks, and already achieved good results. However, these methods ignore the effective use of a large number of existing sentimental resources. For this purpose, we propose a Lexicon-based Sentiment Convolutional Neural Networks (LSCNN) model focus on Weibo's sentiment analysis, which combines two CNNs, trained individually base on sentiment features and word embedding, at the fully connected hidden layer. The experimental results show that our model outperforms the CNN model only with word embedding features on microblog sentiment analysis task.

  7. Enhanced Line Integral Convolution with Flow Feature Detection

    NASA Technical Reports Server (NTRS)

    Lane, David; Okada, Arthur

    1996-01-01

    The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

  8. Tomography by iterative convolution - Empirical study and application to interferometry

    NASA Technical Reports Server (NTRS)

    Vest, C. M.; Prikryl, I.

    1984-01-01

    An algorithm for computer tomography has been developed that is applicable to reconstruction from data having incomplete projections because an opaque object blocks some of the probing radiation as it passes through the object field. The algorithm is based on iteration between the object domain and the projection (Radon transform) domain. Reconstructions are computed during each iteration by the well-known convolution method. Although it is demonstrated that this algorithm does not converge, an empirically justified criterion for terminating the iteration when the most accurate estimate has been computed is presented. The algorithm has been studied by using it to reconstruct several different object fields with several different opaque regions. It also has been used to reconstruct aerodynamic density fields from interferometric data recorded in wind tunnel tests.

  9. Small convolution kernels for high-fidelity image restoration

    NASA Technical Reports Server (NTRS)

    Reichenbach, Stephen E.; Park, Stephen K.

    1991-01-01

    An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

  10. Plane-wave decomposition by spherical-convolution microphone array

    NASA Astrophysics Data System (ADS)

    Rafaely, Boaz; Park, Munhum

    2004-05-01

    Reverberant sound fields are widely studied, as they have a significant influence on the acoustic performance of enclosures in a variety of applications. For example, the intelligibility of speech in lecture rooms, the quality of music in auditoria, the noise level in offices, and the production of 3D sound in living rooms are all affected by the enclosed sound field. These sound fields are typically studied through frequency response measurements or statistical measures such as reverberation time, which do not provide detailed spatial information. The aim of the work presented in this seminar is the detailed analysis of reverberant sound fields. A measurement and analysis system based on acoustic theory and signal processing, designed around a spherical microphone array, is presented. Detailed analysis is achieved by decomposition of the sound field into waves, using spherical Fourier transform and spherical convolution. The presentation will include theoretical review, simulation studies, and initial experimental results.

  11. Star-galaxy classification using deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Kim, Edward J.; Brunner, Robert J.

    2017-02-01

    Most existing star-galaxy classifiers use the reduced summary information from catalogues, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks (ConvNets) allow a machine to automatically learn the features directly from the data, minimizing the need for input from human experts. We present a star-galaxy classification framework that uses deep ConvNets directly on the reduced, calibrated pixel values. Using data from the Sloan Digital Sky Survey and the Canada-France-Hawaii Telescope Lensing Survey, we demonstrate that ConvNets are able to produce accurate and well-calibrated probabilistic classifications that are competitive with conventional machine learning techniques. Future advances in deep learning may bring more success with current and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope, because deep neural networks require very little, manual feature engineering.

  12. Drug-Drug Interaction Extraction via Convolutional Neural Networks

    PubMed Central

    Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong

    2016-01-01

    Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a large number of manually defined features. Recently, convolutional neural networks (CNN), a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%. PMID:26941831

  13. Classification of mitotic figures with convolutional neural networks and seeded blob features

    PubMed Central

    Malon, Christopher D.; Cosatto, Eric

    2013-01-01

    Background: The mitotic figure recognition contest at the 2012 International Conference on Pattern Recognition (ICPR) challenges a system to identify all mitotic figures in a region of interest of hematoxylin and eosin stained tissue, using each of three scanners (Aperio, Hamamatsu, and multispectral). Methods: Our approach combines manually designed nuclear features with the learned features extracted by convolutional neural networks (CNN). The nuclear features capture color, texture, and shape information of segmented regions around a nucleus. The use of a CNN handles the variety of appearances of mitotic figures and decreases sensitivity to the manually crafted features and thresholds. Results: On the test set provided by the contest, the trained system achieves F1 scores up to 0.659 on color scanners and 0.589 on multispectral scanner. Conclusions: We demonstrate a powerful technique combining segmentation-based features with CNN, identifying the majority of mitotic figures with a fair precision. Further, we show that the approach accommodates information from the additional focal planes and spectral bands from a multi-spectral scanner without major redesign. PMID:23858384

  14. Cygrid: A fast Cython-powered convolution-based gridding module for Python

    NASA Astrophysics Data System (ADS)

    Winkel, B.; Lenz, D.; Flöer, L.

    2016-06-01

    Context. Data gridding is a common task in astronomy and many other science disciplines. It refers to the resampling of irregularly sampled data to a regular grid. Aims: We present cygrid, a library module for the general purpose programming language Python. Cygrid can be used to resample data to any collection of target coordinates, although its typical application involves FITS maps or data cubes. The FITS world coordinate system standard is supported. Methods: The regridding algorithm is based on the convolution of the original samples with a kernel of arbitrary shape. We introduce a lookup table scheme that allows us to parallelize the gridding and combine it with the HEALPix tessellation of the sphere for fast neighbor searches. Results: We show that for n input data points, cygrids runtime scales between O(n) and O(nlog n) and analyze the performance gain that is achieved using multiple CPU cores. We also compare the gridding speed with other techniques, such as nearest-neighbor, and linear and cubic spline interpolation. Conclusions: Cygrid is a very fast and versatile gridding library that significantly outperforms other third-party Python modules, such as the linear and cubic spline interpolation provided by SciPy. http://https://github.com/bwinkel/cygrid

  15. Mitochondrial and Metabolic Dysfunction in Renal Convoluted Tubules of Obese Mice: Protective Role of Melatonin

    PubMed Central

    Giugno, Lorena; Lavazza, Antonio; Reiter, Russel J.; Rodella, Luigi Fabrizio; Rezzani, Rita

    2014-01-01

    Obesity is a common and complex health problem, which impacts crucial organs; it is also considered an independent risk factor for chronic kidney disease. Few studies have analyzed the consequence of obesity in the renal proximal convoluted tubules, which are the major tubules involved in reabsorptive processes. For optimal performance of the kidney, energy is primarily provided by mitochondria. Melatonin, an indoleamine and antioxidant, has been identified in mitochondria, and there is considerable evidence regarding its essential role in the prevention of oxidative mitochondrial damage. In this study we evaluated the mechanism(s) of mitochondrial alterations in an animal model of obesity (ob/ob mice) and describe the beneficial effects of melatonin treatment on mitochondrial morphology and dynamics as influenced by mitofusin-2 and the intrinsic apoptotic cascade. Melatonin dissolved in 1% ethanol was added to the drinking water from postnatal week 5–13; the calculated dose of melatonin intake was 100 mg/kg body weight/day. Compared to control mice, obesity-related morphological alterations were apparent in the proximal tubules which contained round mitochondria with irregular, short cristae and cells with elevated apoptotic index. Melatonin supplementation in obese mice changed mitochondria shape and cristae organization of proximal tubules, enhanced mitofusin-2 expression, which in turn modulated the progression of the mitochondria-driven intrinsic apoptotic pathway. These changes possibly aid in reducing renal failure. The melatonin-mediated changes indicate its potential protective use against renal morphological damage and dysfunction associated with obesity and metabolic disease. PMID:25347680

  16. Intervertebral disc segmentation in MR images with 3D convolutional networks

    NASA Astrophysics Data System (ADS)

    Korez, Robert; Ibragimov, Bulat; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

    2017-02-01

    The vertebral column is a complex anatomical construct, composed of vertebrae and intervertebral discs (IVDs) supported by ligaments and muscles. During life, all components undergo degenerative changes, which may in some cases cause severe, chronic and debilitating low back pain. The main diagnostic challenge is to locate the pain generator, and degenerated IVDs have been identified to act as such. Accurate and robust segmentation of IVDs is therefore a prerequisite for computer-aided diagnosis and quantification of IVD degeneration, and can be also used for computer-assisted planning and simulation in spinal surgery. In this paper, we present a novel fully automated framework for supervised segmentation of IVDs from three-dimensional (3D) magnetic resonance (MR) spine images. By considering global intensity appearance and local shape information, a landmark-based approach is first used for the detection of IVDs in the observed image, which then initializes the segmentation of IVDs by coupling deformable models with convolutional networks (ConvNets). For this purpose, a 3D ConvNet architecture was designed that learns rich high-level appearance representations from a training repository of IVDs, and then generates spatial IVD probability maps that guide deformable models towards IVD boundaries. By applying the proposed framework to 15 3D MR spine images containing 105 IVDs, quantitative comparison of the obtained against reference IVD segmentations yielded an overall mean Dice coefficient of 92.8%, mean symmetric surface distance of 0.4 mm and Hausdorff surface distance of 3.7 mm.

  17. Fabrication of Molded Magnetic Article

    NASA Technical Reports Server (NTRS)

    Bryant, Robert G. (Inventor); Namkung, Min (Inventor); Wincheski, Russell A. (Inventor); Fox, Robert L. (Inventor)

    2001-01-01

    A molded magnetic article and fabrication method are provided. Particles of ferromagnetic material embedded in a polymer binder are molded under heat and pressure into a geometric shape. Each particle is an oblate spheroid having a radius-to-thickness aspect ratio approximately in the range of 15-30. Each oblate spheroid has flattened poles that are substantially in perpendicular alignment to a direction of the molding pressure throughout the geometric shape.

  18. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition.

    PubMed

    He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian

    2015-09-01

    Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In this work, we equip the networks with another pooling strategy, "spatial pyramid pooling", to eliminate the above requirement. The new network structure, called SPP-net, can generate a fixed-length representation regardless of image size/scale. Pyramid pooling is also robust to object deformations. With these advantages, SPP-net should in general improve all CNN-based image classification methods. On the ImageNet 2012 dataset, we demonstrate that SPP-net boosts the accuracy of a variety of CNN architectures despite their different designs. On the Pascal VOC 2007 and Caltech101 datasets, SPP-net achieves state-of-the-art classification results using a single full-image representation and no fine-tuning. The power of SPP-net is also significant in object detection. Using SPP-net, we compute the feature maps from the entire image only once, and then pool features in arbitrary regions (sub-images) to generate fixed-length representations for training the detectors. This method avoids repeatedly computing the convolutional features. In processing test images, our method is 24-102 × faster than the R-CNN method, while achieving better or comparable accuracy on Pascal VOC 2007. In ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2014, our methods rank #2 in object detection and #3 in image classification among all 38 teams. This manuscript also introduces the improvement made for this competition.

  19. Modeling Task fMRI Data via Deep Convolutional Autoencoder.

    PubMed

    Huang, Heng; Hu, Xintao; Zhao, Yu; Makkie, Milad; Dong, Qinglin; Zhao, Shijie; Guo, Lei; Liu, Tianming

    2017-06-15

    Task-based fMRI (tfMRI) has been widely used to study functional brain networks under task performance. Modeling tfMRI data is challenging due to at least two problems: the lack of the ground truth of underlying neural activity and the highly complex intrinsic structure of tfMRI data. To better understand brain networks based on fMRI data, data-driven approaches have been proposed, for instance, Independent Component Analysis (ICA) and Sparse Dictionary Learning (SDL). However, both ICA and SDL only build shallow models, and they are under the strong assumption that original fMRI signal could be linearly decomposed into time series components with their corresponding spatial maps. As growing evidence shows that human brain function is hierarchically organized, new approaches that can infer and model the hierarchical structure of brain networks are widely called for. Recently, deep convolutional neural network (CNN) has drawn much attention, in that deep CNN has proven to be a powerful method for learning high-level and mid-level abstractions from low-level raw data. Inspired by the power of deep CNN, in this study, we developed a new neural network structure based on CNN, called Deep Convolutional Auto-Encoder (DCAE), in order to take the advantages of both data-driven approach and CNN's hierarchical feature abstraction ability for the purpose of learning mid-level and high-level features from complex, large-scale tfMRI time series in an unsupervised manner. The DCAE has been applied and tested on the publicly available human connectome project (HCP) tfMRI datasets, and promising results are achieved.

  20. Fovea detection in optical coherence tomography using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Liefers, Bart; Venhuizen, Freerk G.; Theelen, Thomas; Hoyng, Carel; van Ginneken, Bram; Sánchez, Clara I.

    2017-02-01

    The fovea is an important clinical landmark that is used as a reference for assessing various quantitative measures, such as central retinal thickness or drusen count. In this paper we propose a novel method for automatic detection of the foveal center in Optical Coherence Tomography (OCT) scans. Although the clinician will generally aim to center the OCT scan on the fovea, post-acquisition image processing will give a more accurate estimate of the true location of the foveal center. A Convolutional Neural Network (CNN) was trained on a set of 781 OCT scans that classifies each pixel in the OCT B-scan with a probability of belonging to the fovea. Dilated convolutions were used to obtain a large receptive field, while maintaining pixel-level accuracy. In order to train the network more effectively, negative patches were sampled selectively after each epoch. After CNN classification of the entire OCT volume, the predicted foveal center was chosen as the voxel with maximum output probability, after applying an optimized three-dimensional Gaussian blurring. We evaluate the performance of our method on a data set of 99 OCT scans presenting different stages of Age-related Macular Degeneration (AMD). The fovea was correctly detected in 96:9% of the cases, with a mean distance error of 73 μm(+/-112 μm). This result was comparable to the performance of a second human observer who obtained a mean distance error of 69 μm (+/-94 μm). Experiments showed that the proposed method is accurate and robust even in retinas heavily affected by pathology.

  1. Self-shaping of bioinspired chiral composites

    NASA Astrophysics Data System (ADS)

    Rong, Qing-Qing; Cui, Yu-Hong; Shimada, Takahiro; Wang, Jian-Shan; Kitamura, Takayuki

    2014-08-01

    Self-shaping materials such as shape memory polymers have recently drawn considerable attention owing to their high shape-changing ability in response to changes in ambient conditions, and thereby have promising applications in the biomedical, biosensing, soft robotics and aerospace fields. Their design is a crucial issue of both theoretical and technological interest. Motivated by the shape-changing ability of Towel Gourd tendril helices during swelling/deswelling, we present a strategy for realizing self-shaping function through the deformation of micro/nanohelices. To guide the design and fabrication of self-shaping materials, the shape equations of bent configurations, twisted belts, and helices of slender chiral composite are developed using the variation method. Furthermore, it is numerically shown that the shape changes of a chiral composite can be tuned by the deformation of micro/nanohelices and the fabricated fiber directions. This work paves a new way to create self-shaping composites.

  2. Some physical factors influencing the accuracy of convolution scatter correction in SPECT.

    PubMed

    Msaki, P; Axelsson, B; Larsson, S A

    1989-03-01

    Some important physical factors influencing the accuracy of convolution scatter correction techniques in SPECT are presented. In these techniques scatter correction in the projection relies on filter functions, QF, evaluated by Fourier transforms, from measured scatter functions, Qp, obtained from point spread functions. The spatial resolution has a marginal effect on Qp. Thus a single QF can be used in the scatter correction of SPECT measurements acquired with the low energy high resolution or the low energy general purpose collimators and over a wide range of patient-collimator distances. However, it is necessary to examine the details of the shape of point spread functions during evaluation of Qp. QF is completely described by scatter amplitude AF, slope BF and filter sum SF. SF is obtained by summation of the values of QF occupying a 31 x 31 pixels matrix. Regardless of differences in amplitude and slope, two filter functions are shown to be equivalent in terms of scatter correction ability, whenever their sums are equal. On the basis of filter sum, the observed small influence of ellipticity on QF implies that an average function can be used in scatter correcting SPECT measurements conducted with elliptic objects. SF is shown to increase with a decrease in photon energy and with an increase in window size. Thus, scatter correction by convolution may be severely hampered by photon statistics when SPECT imaging is done with low-energy photons. It is pointless to use unnecessarily large discriminator windows, in the hope of improving photon statistics, since most of the extra events acquired will eventually be subtracted during scatter correction. Regardless of the observed moderate reduction in SF when a lung-equivalent material replaces a portion of a water phantom, further studies are needed to develop a technique that is capable of handling attenuation and scatter corrections simultaneously. Whenever superficial and inner radioactive distributions coexist the

  3. Directed light fabrication

    SciTech Connect

    Lewis, G.K.; Nemec, R.; Milewski, J.; Thoma, D.J.; Cremers, D.; Barbe, M.

    1994-09-01

    Directed Light Fabrication (DLF) is a rapid prototyping process being developed at Los Alamos National Laboratory to fabricate metal components. This is done by fusing gas delivered metal powder particles in the focal zone of a laser beam that is, programmed to move along or across the part cross section. Fully dense metal is built up a layer at a time to form the desired part represented by a 3 dimensional solid model from CAD software. Machine ``tool paths`` are created from the solid model that command the movement and processing parameters specific to the DLF process so that the part can be built one layer at a time. The result is a fully dense, near net shape metal part that solidifies under rapid solidification conditions.

  4. Directed light fabrication

    NASA Astrophysics Data System (ADS)

    Lewis, G. K.; Nemec, R.; Milewski, J.; Thoma, D. J.; Cremers, D.; Barbe, M.

    1994-09-01

    Directed Light Fabrication (DLF) is a rapid prototyping process being developed at Los Alamos National Laboratory to fabricate metal components. This is done by fusing gas delivered metal powder particles in the focal zone of a laser beam that is programmed to move along or across the part cross section. Fully dense metal is built up a layer at a time to form the desired part represented by a 3 dimensional solid model from CAD software. Machine 'tool paths' are created from the solid model that command the movement and processing parameters specific to the DLF process so that the part can be built one layer at a time. The result is a fully dense, near net shape metal part that solidifies under rapid solidification conditions.

  5. Optimal convolution SOR acceleration of waveform relaxation with application to semiconductor device simulation

    NASA Technical Reports Server (NTRS)

    Reichelt, Mark

    1993-01-01

    In this paper we describe a novel generalized SOR (successive overrelaxation) algorithm for accelerating the convergence of the dynamic iteration method known as waveform relaxation. A new convolution SOR algorithm is presented, along with a theorem for determining the optimal convolution SOR parameter. Both analytic and experimental results are given to demonstrate that the convergence of the convolution SOR algorithm is substantially faster than that of the more obvious frequency-independent waveform SOR algorithm. Finally, to demonstrate the general applicability of this new method, it is used to solve the differential-algebraic system generated by spatial discretization of the time-dependent semiconductor device equations.

  6. Fabrication of metallic glass structures

    DOEpatents

    Cline, Carl F.

    1986-01-01

    Amorphous metal powders or ribbons are fabricated into solid shapes of appreciable thickness by the application of compaction energy. The temperature regime wherein the amorphous metal deforms by viscous flow is measured. The metal powders or ribbons are compacted within the temperature range.

  7. Fabrication of metallic glass structures

    DOEpatents

    Cline, C.F.

    1983-10-20

    Amorphous metal powders or ribbons are fabricated into solid shapes of appreciable thickness by the application of compaction energy. The temperature regime wherein the amorphous metal deforms by viscous flow is measured. The metal powders or ribbons are compacted within the temperature regime.

  8. [An improvement on the two-dimensional convolution method of image reconstruction and its application to SPECT].

    PubMed

    Suzuki, S; Arai, H

    1990-04-01

    In single-photon emission computed tomography (SPECT) and X-ray CT one-dimensional (1-D) convolution method is used for their image reconstruction from projections. The method makes a 1-D convolution filtering on projection data with a 1-D filter in the space domain, and back projects the filtered data for reconstruction. Images can also be reconstructed by first forming the 2-D backprojection images from projections and then convoluting them with a 2-D space-domain filter. This is the reconstruction by the 2-D convolution method, and it has the opposite reconstruction process to the 1-D convolution method. Since the 2-D convolution method is inferior to the 1-D convolution method in speed in reconstruction, it has no practical use. In the actual reconstruction by the 2-D convolution method, convolution is made on a finite plane which is called convolution window. A convolution window of size N X N needs a 2-D discrete filter of the same size. If better reconstructions are achieved with small convolution windows, the reconstruction time for the 2-D convolution method can be reduced. For this purpose, 2-D filters of a simple function form are proposed which can give good reconstructions with small convolution windows. They are here defined on a finite plane, depending on the window size used, although a filter function is usually defined on the infinite plane. They are however set so that they better approximate the property of a 2-D filter function defined on the infinite plane. Filters of size N X N are thus determined. Their value varies with window size. The filters are applied to image reconstructions of SPECT.(ABSTRACT TRUNCATED AT 250 WORDS)

  9. Fabrication of tungsten wire reinforced nickel-base alloy composites

    NASA Technical Reports Server (NTRS)

    Brentnall, W. D.; Toth, I. J.

    1974-01-01

    Fabrication methods for tungsten fiber reinforced nickel-base superalloy composites were investigated. Three matrix alloys in pre-alloyed powder or rolled sheet form were evaluated in terms of fabricability into composite monotape and multi-ply forms. The utility of monotapes for fabricating more complex shapes was demonstrated. Preliminary 1093C (2000F) stress rupture tests indicated that efficient utilization of fiber strength was achieved in composites fabricated by diffusion bonding processes. The fabrication of thermal fatigue specimens is also described.

  10. Convoluted nozzle design for the RL10 derivative 2B engine

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The convoluted nozzle is a conventional refractory metal nozzle extension that is formed with a portion of the nozzle convoluted to show the extendible nozzle within the length of the rocket engine. The convoluted nozzle (CN) was deployed by a system of four gas driven actuators. For spacecraft applications the optimum CN may be self-deployed by internal pressure retained, during deployment, by a jettisonable exit closure. The convoluted nozzle is included in a study of extendible nozzles for the RL10 Engine Derivative 2B for use in an early orbit transfer vehicle (OTV). Four extendible nozzle configurations for the RL10-2B engine were evaluated. Three configurations of the two position nozzle were studied including a hydrogen dump cooled metal nozzle and radiation cooled nozzles of refractory metal and carbon/carbon composite construction respectively.

  11. Directional Radiometry and Radiative Transfer: the Convoluted Path From Centuries-old Phenomenology to Physical Optics

    NASA Technical Reports Server (NTRS)

    Mishchenko, Michael I.

    2014-01-01

    This Essay traces the centuries-long history of the phenomenological disciplines of directional radiometry and radiative transfer in turbid media, discusses their fundamental weaknesses, and outlines the convoluted process of their conversion into legitimate branches of physical optics.

  12. Operational and convolution properties of two-dimensional Fourier transforms in polar coordinates.

    PubMed

    Baddour, Natalie

    2009-08-01

    For functions that are best described in terms of polar coordinates, the two-dimensional Fourier transform can be written in terms of polar coordinates as a combination of Hankel transforms and Fourier series-even if the function does not possess circular symmetry. However, to be as useful as its Cartesian counterpart, a polar version of the Fourier operational toolset is required for the standard operations of shift, multiplication, convolution, etc. This paper derives the requisite polar version of the standard Fourier operations. In particular, convolution-two dimensional, circular, and radial one dimensional-is discussed in detail. It is shown that standard multiplication/convolution rules do apply as long as the correct definition of convolution is applied.

  13. Convolution of large 3D images on GPU and its decomposition

    NASA Astrophysics Data System (ADS)

    Karas, Pavel; Svoboda, David

    2011-12-01

    In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach efficient in terms of both time and memory consumption and also in terms of memory transfers between CPU and GPU which have a significant inuence on overall computational time. We also study the implementation on multiple GPUs and compare the results between the multi-GPU and multi-CPU implementations.

  14. Error Analysis of Padding Schemes for DFT’s of Convolutions and Derivatives

    DTIC Science & Technology

    2012-01-31

    Geodaetica, 18,263-279. Oppenheim AV, Schafer RW (1975) Digital Signal Processing . Prentice-Hall, Inc., Englewood Cliffs, New Jersey. Schwarz KP... Oppenheim and Schäfer (1975). Many numerical tests have been done to show that this so-called zero padding improves the computation of Stokes...and (19) relate linear convolutions to corresponding cyclic convolutions. Equation (19) is the justification, originating in Oppenheim and Schäfer

  15. A convolution model for computing the far-field directivity of a parametric loudspeaker array.

    PubMed

    Shi, Chuang; Kajikawa, Yoshinobu

    2015-02-01

    This paper describes a method to compute the far-field directivity of a parametric loudspeaker array (PLA), whereby the steerable parametric loudspeaker can be implemented when phased array techniques are applied. The convolution of the product directivity and the Westervelt's directivity is suggested, substituting for the past practice of using the product directivity only. Computed directivity of a PLA using the proposed convolution model achieves significant improvement in agreement to measured directivity at a negligible computational cost.

  16. Determining micro- and macro- geometry of fabric and fabric reinforced composites

    NASA Astrophysics Data System (ADS)

    Huang, Lejian

    Textile composites are made from textile fabric and resin. Depending on the weaving pattern, composite reinforcements can be characterized into two groups: uniform fabric and near-net shape fabric. Uniform fabric can be treated as an assembly of its smallest repeating pattern also called a unit cell; the latter is a single component with complex structure. Due to advantages of cost savings and inherent toughness, near-net shape fabric has gained great success in composite industries, for application such as turbine blades. Mechanical properties of textile composites are mainly determined by the geometry of the composite reinforcements. The study of a composite needs a computational tool to link fabric micro- and macro-geometry with the textile weaving process and composite manufacturing process. A textile fabric consists of a number of yarns or tows, and each yarn is a bundle of fibers. In this research, a fiber-level approach known as the digital element approach (DEA) is adopted to model the micro- and macro-geometry of fabric and fabric reinforced composites. This approach determines fabric geometry based on textile weaving mechanics. A solver with a dynamic explicit algorithm is employed in the DEA. In modeling a uniform fabric, the topology of the fabric unit cell is first established based on the weaving pattern, followed by yarn discretization. An explicit algorithm with a periodic boundary condition is then employed during the simulation. After its detailed geometry is obtained, the unit cell is then assembled to yield a fabric micro-geometry. Fabric micro-geometry can be expressed at both fiber- and yarn-levels. In modeling a near-net shape fabric component, all theories used in simulating the uniform fabric are kept except the periodic boundary condition. Since simulating the entire component at the fiber-level requires a large amount of time and memory, parallel program is used during the simulation. In modeling a net-shape composite, a dynamic molding

  17. Fabrication Technology

    SciTech Connect

    Blaedel, K.L.

    1993-03-01

    The mission of the Fabrication Technology thrust area is to have an adequate base of manufacturing technology, not necessarily resident at Lawrence Livermore National Laboratory (LLNL), to conduct the future business of LLNL. The specific goals continue to be to (1) develop an understanding of fundamental fabrication processes; (2) construct general purpose process models that will have wide applicability; (3) document findings and models in journals; (4) transfer technology to LLNL programs, industry, and colleagues; and (5) develop continuing relationships with the industrial and academic communities to advance the collective understanding of fabrication processes. The strategy to ensure success is changing. For technologies in which they are expert and which will continue to be of future importance to LLNL, they can often attract outside resources both to maintain their expertise by applying it to a specific problem and to help fund further development. A popular vehicle to fund such work is the Cooperative Research and Development Agreement with industry. For technologies needing development because of their future critical importance and in which they are not expert, they use internal funding sources. These latter are the topics of the thrust area. Three FY-92 funded projects are discussed in this section. Each project clearly moves the Fabrication Technology thrust area towards the goals outlined above. They have also continued their membership in the North Carolina State University Precision Engineering Center, a multidisciplinary research and graduate program established to provide the new technologies needed by high-technology institutions in the US. As members, they have access to and use of the results of their research projects, many of which parallel the precision engineering efforts at LLNL.

  18. Minimal-memory realization of pearl-necklace encoders of general quantum convolutional codes

    SciTech Connect

    Houshmand, Monireh; Hosseini-Khayat, Saied

    2011-02-15

    Quantum convolutional codes, like their classical counterparts, promise to offer higher error correction performance than block codes of equivalent encoding complexity, and are expected to find important applications in reliable quantum communication where a continuous stream of qubits is transmitted. Grassl and Roetteler devised an algorithm to encode a quantum convolutional code with a ''pearl-necklace'' encoder. Despite their algorithm's theoretical significance as a neat way of representing quantum convolutional codes, it is not well suited to practical realization. In fact, there is no straightforward way to implement any given pearl-necklace structure. This paper closes the gap between theoretical representation and practical implementation. In our previous work, we presented an efficient algorithm to find a minimal-memory realization of a pearl-necklace encoder for Calderbank-Shor-Steane (CSS) convolutional codes. This work is an extension of our previous work and presents an algorithm for turning a pearl-necklace encoder for a general (non-CSS) quantum convolutional code into a realizable quantum convolutional encoder. We show that a minimal-memory realization depends on the commutativity relations between the gate strings in the pearl-necklace encoder. We find a realization by means of a weighted graph which details the noncommutative paths through the pearl necklace. The weight of the longest path in this graph is equal to the minimal amount of memory needed to implement the encoder. The algorithm has a polynomial-time complexity in the number of gate strings in the pearl-necklace encoder.

  19. Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

    PubMed

    Witoonchart, Peerajak; Chongstitvatana, Prabhas

    2017-08-01

    In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. A quantum algorithm for Viterbi decoding of classical convolutional codes

    NASA Astrophysics Data System (ADS)

    Grice, Jon R.; Meyer, David A.

    2015-07-01

    We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper, the proposed algorithm is applied to decoding classical convolutional codes, for instance, large constraint length and short decode frames . Other applications of the classical Viterbi algorithm where is large (e.g., speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butterfly diagram of the fast Fourier transform, with its corresponding fast quantum algorithm. The tensor-product structure of the butterfly diagram corresponds to a quantum superposition that we show can be efficiently prepared. The quantum speedup is possible because the performance of the QVA depends on the fanout (number of possible transitions from any given state in the hidden Markov model) which is in general much less than . The QVA constructs a superposition of states which correspond to all legal paths through the decoding lattice, with phase as a function of the probability of the path being taken given received data. A specialized amplitude amplification procedure is applied one or more times to recover a superposition where the most probable path has a high probability of being measured.